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  • Articles  (274)
  • optimal control  (157)
  • global optimization  (117)
  • Springer  (274)
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  • Mathematics  (274)
  • 1
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    Annals of operations research 98 (2000), S. 45-64 
    ISSN: 1572-9338
    Keywords: optimal control ; partial differential equations ; numerical methods ; transdermal systems ; acetylene reactors
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We present an approach to compute optimal control functions in dynamic models based on one-dimensional partial differential algebraic equations (PDAE). By using the method of lines, the PDAE is transformed into a large system of usually stiff ordinary differential algebraic equations and integrated by standard methods. The resulting nonlinear programming problem is solved by the sequential quadratic programming code NLPQL. Optimal control functions are approximated by piecewise constant, piecewise linear or bang-bang functions. Three different types of cost functions can be formulated. The underlying model structure is quite flexible. We allow break points for model changes, disjoint integration areas with respect to spatial variable, arbitrary boundary and transition conditions, coupled ordinary and algebraic differential equations, algebraic equations in time and space variables, and dynamic constraints for control and state variables. The PDAE is discretized by difference formulae, polynomial approximations with arbitrary degrees, and by special update formulae in case of hyperbolic equations. Two application problems are outlined in detail. We present a model for optimal control of transdermal diffusion of drugs, where the diffusion speed is controlled by an electric field, and a model for the optimal control of the input feed of an acetylene reactor given in form of a distributed parameter system.
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  • 2
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    Annals of operations research 98 (2000), S. 65-87 
    ISSN: 1572-9338
    Keywords: train control ; optimal control ; discrete control ; optimal switching times
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We consider the problem of determining an optimal driving strategy in a train control problem with a generalised equation of motion. We assume that the journey must be completed within a given time and seek a strategy that minimises fuel consumption. On the one hand we consider the case where continuous control can be used and on the other hand we consider the case where only discrete control is available. We pay particular attention to a unified development of the two cases. For the continuous control problem we use the Pontryagin principle to find necessary conditions on an optimal strategy and show that these conditions yield key equations that determine the optimal switching points. In the discrete control problem, which is the typical situation with diesel-electric locomotives, we show that for each fixed control sequence the cost of fuel can be minimised by finding the optimal switching times. The corresponding strategies are called strategies of optimal type and in this case we use the Kuhn–Tucker equations to find key equations that determine the optimal switching times. We note that the strategies of optimal type can be used to approximate as closely as we please the optimal strategy obtained using continuous control and we present two new derivations of the key equations. We illustrate our general remarks by reference to a typical train control problem.
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  • 3
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    Annals of operations research 98 (2000), S. 171-187 
    ISSN: 1572-9338
    Keywords: global optimization ; cutting angle method ; increasing positively homogeneous function
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract In this paper we study a method for global optimization of increasing positively homogeneous functions over the unit simplex, which is a version of the cutting angle method. Some properties of the auxiliary subproblem are studied and a special algorithm for its solution is proposed. A cutting angle method based on this algorithm allows one to find an approximate solution of some problems of global optimization with 50 variables. Results of numerical experiments are discussed.
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    Annals of operations research 98 (2000), S. 333-351 
    ISSN: 1572-9338
    Keywords: production planning ; stochastic dynamic programming ; optimal control ; long-run average cost
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We consider a production planning problem in a two-machine flowshop subject to breakdown and repair of machines and subject to nonnegativity and upper bound constraints on work-in-process. The objective is to choose machine production rates over time to minimize the long-run average inventory/backlog and production costs. For sufficiently large upper bound on the work-in-process, the problem is formulated as a stochastic dynamic program. We then establish a verification theorem and a partial characterization of the optimal control policy if it exists.
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  • 5
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    Journal of heuristics 6 (2000), S. 191-213 
    ISSN: 1572-9397
    Keywords: genetic algorithm ; global optimization ; continuous variables
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Genetic algorithms are stochastic search approaches based on randomized operators, such as selection, crossover and mutation, inspired by the natural reproduction and evolution of the living creatures. However, few published works deal with their application to the global optimization of functions depending on continuous variables. A new algorithm called Continuous Genetic Algorithm (CGA) is proposed for the global optimization of multiminima functions. In order to cover a wide domain of possible solutions, our algorithm first takes care over the choice of the initial population. Then it locates the most promising area of the solution space, and continues the search through an “intensification” inside this area. The selection, the crossover and the mutation are performed by using the decimal code. The efficiency of CGA is tested in detail through a set of benchmark multimodal functions, of which global and local minima are known. CGA is compared to Tabu Search and Simulated Annealing, as alternative algorithms.
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    Journal of heuristics 6 (2000), S. 405-418 
    ISSN: 1572-9397
    Keywords: MOCO ; multiobjective optimization ; global optimization ; local search methods ; metaheuristics ; quad-trees
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper presents a new concept for generating approximations to the non-dominated set in multiobjective optimization problems. The approximation set A is constructed by solving several single-objective minimization problems in which a particular function D(A, z) is minimized. A new algorithm to calculate D(A, z) is proposed. No general approach is available to solve the one-dimensional optimization problems, but metaheuristics based on local search procedures are used instead. Tests with multiobjective combinatorial problems whose non-dominated sets are known confirm that CHESS can be used to approximate the non-dominated set. Straightforward parallelization of the CHESS approach is illustrated with examples. The algorithm to calculate D(A, z) can be used in any other applications that need to determine Tchebycheff distances between a point and a dominant-free set.
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  • 7
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    Set-valued analysis 8 (2000), S. 31-50 
    ISSN: 1572-932X
    Keywords: stability in optimization ; generalized equations ; Lipschitz continuity ; mathematical programming ; optimal control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We study two continuity concepts for set-valued maps that play central roles in quantitative stability analysis of optimization problems: Aubin continuity and Lipschitzian localization. We show that various inverse function theorems involving these concepts can be deduced from a single general result on existence of solutions to an inclusion in metric spaces. As applications, we analyze the stability with respect to canonical perturbations of a mathematical program in a Hilbert space and an optimal control problem with inequality control constraints. For stationary points of these problems, Aubin continuity and Lipschitzian localization coincide; moreover, both properties are equivalent to surjectivity of the map of the gradients of the active constraints combined with a strong second-order sufficient optimality condition.
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  • 8
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    Set-valued analysis 8 (2000), S. 111-126 
    ISSN: 1572-932X
    Keywords: viability ; optimal control ; value function
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper we explain that various (possibly discontinuous) value functions for optimal control problem under state-constraints can be approached by a sequence of value functions for suitable discretized systems. The key-point of this approach is the characterization of epigraphs of the value functions as suitable viability kernels. We provide new results for estimation of the convergence rate of numerical schemes and discuss conditions for the convergence of discrete optimal controls to the optimal control for the initial problem.
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  • 9
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    Annals of operations research 98 (2000), S. 19-44 
    ISSN: 1572-9338
    Keywords: optimal control ; nonlinear systems ; parabolic systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract We consider first nonlinear systems of the form x=A(x)x+B(x)u together with a standard quadratic cost functional and replace the system by a sequence of time-varying approximations for which the optimal control problem can be solved explicitly. We then show that the sequence converges. Although it may not converge to a global optimal control of the nonlinear system, we also consider a similar approximation sequence for the equation given by the necessary conditions of the maximum principle and we shall see that the first method gives solutions very close to the optimal solution in many cases. We shall also extend the results to parabolic PDEs which can be written in the above form on some Hilbert space.
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  • 10
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    Journal of optimization theory and applications 104 (2000), S. 301-322 
    ISSN: 1573-2878
    Keywords: global optimization ; multiplicative programming ; cutting plane ; nonconvex programming ; outcome space ; extreme-point search
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This article presents an outcome-space pure cutting-plane algorithm for globally solving the linear multiplicative programming problem. The framework of the algorithm is taken from a pure cutting-plane decision set-based method developed by Horst and Tuy for solving concave minimization problems. By adapting this method to an outcome-space reformulation of the linear multiplicative programming problem, rather than applying directly the method to the original decision-set formulation, it is expected that considerable computational savings can be obtained. Also, we show how additional computational benefits might be obtained by implementing the new algorithm appropriately. To illustrate the new algorithm, we apply it to the solution of a sample problem.
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  • 11
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    Journal of optimization theory and applications 105 (2000), S. 263-276 
    ISSN: 1573-2878
    Keywords: optimal control ; distributed-parameter systems ; Pontryagin maximum principle ; Ekeland variational principle ; unbounded controls
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We prove the maximum principle for an optimal control problem governed by the system $$y'(t) + A(t)y(t) = f(t,y(t),u(t)),{\text{ }}u(t) \in U(t), $$ with state constraint $$(y(0),y(T)) \in C \subset H \times H $$ , under three different hypotheses: (H1) C is a convex set with nonempty interior; (H2) $$C = \{ y_0 \} \times C_{0,} {\text{ with }}C_0 $$ a convex set with nonempty interior in H and the evolution system satisfying compactness hypotheses; (H3) the periodic case $$y(0) = y(T)$$ , with the evolution system satisfying compactness hypotheses. We do not assume the controls to be bounded. We give some examples for distributed control problems.
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  • 12
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    Journal of optimization theory and applications 106 (2000), S. 231-264 
    ISSN: 1573-2878
    Keywords: hierarchical control ; manufacturing systems ; stochastic dynamic programming ; optimal control ; long-run average cost
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We consider a production planning problem for a dynamic jobshop producing a number of products and subject to breakdown and repair of machines. The machine capacities are assumed to be finite-state Markov chains. As the rates of change of the machine states approach infinity, an asymptotic analysis of this stochastic manufacturing systems is given. The analysis results in a limiting problem in which the stochastic machine availability is replaced by its equilibrium mean availability. The long-run average cost for the original problem is shown to converge to the long-run average cost of the limiting problem. The convergence rate of the long-run average cost for the original problem to that of the limiting problem together with an error estimate for the constructed asymptotic optimal control is established.
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  • 13
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    Journal of optimization theory and applications 106 (2000), S. 627-655 
    ISSN: 1573-2878
    Keywords: variational inequalities ; optimal control ; state constraint ; maximum principle
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This work deals with the necessary conditions of optimality for some optimal control problems governed by elliptic variational inequalities. Boundary control and state constrained problems are considered. The techniques used are based on those in Ref. 1 and a new penalty functional is defined in this paper.
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  • 14
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    Journal of optimization theory and applications 107 (2000), S. 391-414 
    ISSN: 1573-2878
    Keywords: diffusion networks ; image estimation ; global optimization ; simulated annealing ; weak convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This work is concerned with a numerical procedure for approximating an analog diffusion network. The key idea is to take advantage of the separable feature of the noise for the diffusion machine and use a parallel processing method to develop recursive algorithms. The asymptotic properties are studied. The main result of this paper is to establish the convergence of a continuous-time interpolation of the discrete-time algorithm to that of the analog diffusion network via weak convergence methods. The parallel processing feature of the network makes it attractive for solving large-scale optimization problems. Applications to image estimation are considered. Not only is this algorithm useful for the image estimation problems, but it is widely applicable to many related optimization problems.
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  • 15
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    Journal of optimization theory and applications 107 (2000), S. 331-354 
    ISSN: 1573-2878
    Keywords: general quadratic programming problem with quadratic constraints ; global optimization ; branch-and-bound algorithms ; duality bounds
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The purpose of this article is to develop a branch-and-bound algorithm using duality bounds for the general quadratically-constrained quadratic programming problem and having the following properties: (i) duality bounds are computed by solving ordinary linear programs; (ii) they are at least as good as the lower bounds obtained by solving relaxed problems, in which each nonconvex function is replaced by its convex envelope; (iii) standard convergence properties of branch-and-bound algorithms for nonconvex global optimization problems are guaranteed. Numerical results of preliminary computational experiments for the case of one quadratic constraint are reported.
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  • 16
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    Journal of optimization theory and applications 107 (2000), S. 275-286 
    ISSN: 1573-2878
    Keywords: optimal control ; thresholds ; multiple equilibria ; instability ; concavity
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract An important and numerous literature argues that nonconcavity (often convexity with respect to the state) of the Hamiltonian leads to multiple steady states, instability, and a threshold. This threshold property provides a powerful paradigm to explain history dependency and hysteresis. This paper shows that economically relevant properties (in particular, multiple steady states and thresholds) are possible in strict concave models too. Two corresponding necessary conditions with intuitive economic interpretation are derived.
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  • 17
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    Optimization and engineering 1 (2000), S. 373-397 
    ISSN: 1573-2924
    Keywords: global optimization ; nonconvex optimization ; software ; black box
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Technology
    Notes: Abstract The paper considers global optimization of costly objective functions, i.e. the problem of finding the global minimum when there are several local minima and each function value takes considerable CPU time to compute. Such problems often arise in industrial and financial applications, where a function value could be a result of a time-consuming computer simulation or optimization. Derivatives are most often hard to obtain, and the algorithms presented make no use of such information. Several algorithms to handle the global optimization problem are described, but the emphasis is on a new method by Gutmann and Powell, A radial basis function method for global optimization. This method is a response surface method, similar to the Efficient Global Optimization (EGO) method of Jones. Our Matlab implementation of the Radial Basis Function (RBF) method is described in detail and we analyze its efficiency on the standard test problem set of Dixon-Szegö, as well as its applicability on a real life industrial problem from train design optimization. The results show that our implementation of the RBF algorithm is very efficient on the standard test problems compared to other known solvers, but even more interesting, it performs extremely well on the train design optimization problem.
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  • 18
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    Applied mathematics and mechanics 21 (2000), S. 1161-1168 
    ISSN: 1573-2754
    Keywords: space manipulator ; motion planning ; optimal control ; wavelet analysis ; TP241
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Mathematics , Physics
    Notes: Abstract The optimal control problem of nonholonomic motion planning of space manipulator was discussed. Utilizing the method of wavelet analysis, the discrete orthogonal wavelets were introduced to solve the optimal control problem, the classical Fourier basic functions were replaced by the wavelet expansion approximation. A numerical algorithm of optimal control was proposed based on wavelet analysis. The numerical simulation shows, the method is effective for nonholonomic motion planning of space manitulator.
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    Journal of optimization theory and applications 104 (2000), S. 343-376 
    ISSN: 1573-2878
    Keywords: random search ; stochastic approximation ; global optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A new recursive algorithm for searching the global minimizer of a function is proposed when the function is observed with noise. The algorithm is based on switches between the stochastic approximation and the random search. The combination of SA with RS is not a new idea in such combination, the difficulty consists in creating a good switching rule and in designing an efficient method to reduce the noise effect. The proposed switching rule is easily realizable, the noise reducing method is effective, and the whole recursive optimization algorithm is simply calculated. It is proved that the algorithm a.s. converges to the global minimizer and is asymptotically normal. In comparison with existing methods, the proposed algorithm not only requires much weaker conditions, but also is more efficient as shown by simulation.
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    Journal of optimization theory and applications 104 (2000), S. 691-716 
    ISSN: 1573-2878
    Keywords: simulated annealing ; cooling schedule ; global optimization ; convergence analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A class of simulated annealing algorithms for continuous global optimization is considered in this paper. The global convergence property is analyzed with respect to the objective value sequence and the minimum objective value sequence induced by simulated annealing algorithms. The convergence analysis provides the appropriate conditions on both the generation probability density function and the temperature updating function. Different forms of temperature updating functions are obtained with respect to different kinds of generation probability density functions, leading to different types of simulated annealing algorithms which all guarantee the convergence to the global optimum.
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    Journal of optimization theory and applications 105 (2000), S. 55-72 
    ISSN: 1573-2878
    Keywords: optimal control ; bilinear systems ; nilpotent Lie algebra ; products of exponentials
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper derives some optimization results for bilinear systems using a higher-order method by characterizing them over matrix Lie groups. In the derivation of the results, first a bilinear system is transformed to a left-invariant system on matrix Lie groups. Then, the product of exponential representation is used to express this system in canonical form. Next, the conditions for optimality are obtained by the principles of variational calculus. It is demonstrated that closed-form analytical solutions exist for classes of bilinear systems whose Lie algebra are nilpotent.
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    Journal of optimization theory and applications 105 (2000), S. 441-455 
    ISSN: 1573-2878
    Keywords: expenditure patterns ; research and development ; optimal control ; calculus of variations
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The optimal expenditure pattern for a double-path engineering project, i.e., a project composed of a nonroutine risky R&D path and a routine nonrisky preparatory path, manufacturing related or marketing related, is studied via the calculus of variations to derive a set of twin second-order nonlinear differential equations whose solution yields the optimal joint expenditure. Assuming independence between the risky and nonrisky paths, a constant return per unit time, a gamma-type unimodal conditional-completion density function for the R&D activity, and the principle of diminishing returns on the effort, we find an interesting interplay between the two paths for the peak position and termination of the expenditures. Counterintuitively, we find that the peak expenditure of the R&D path does not necessarily precede that of the preparatory path, although both path expenditure peaks obey the well-known Kamien–Schwartz theorem. That is, for both paths, the expenditure peak positions precede always the peak of the conditional-completion density function of the R&D path.
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    Journal of optimization theory and applications 107 (2000), S. 355-389 
    ISSN: 1573-2878
    Keywords: global optimization ; reverse convex programming problem ; dual problem ; inner approximation method ; penalty function method
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, we consider a reverse convex programming problem constrained by a convex set and a reverse convex set, which is defined by the complement of the interior of a compact convex set X. We propose an inner approximation method to solve the problem in the case where X is not necessarily a polytope. The algorithm utilizes an inner approximation of X by a sequence of polytopes to generate relaxed problems. It is shown that every accumulation point of the sequence of optimal solutions of the relaxed problems is an optimal solution of the original problem.
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    Journal of optimization theory and applications 107 (2000), S. 245-260 
    ISSN: 1573-2878
    Keywords: global optimization ; difference of convex functions ; location theory ; multiple-criteria decision making
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    Topics: Mathematics
    Notes: Abstract In this paper, we show that a DC representation can be obtained explicitly for the composition of a gauge with a DC mapping, so that the optimization of certain functions involving terms of this kind can be made by using standard DC optimization techniques. Applications to facility location theory and multiple-criteria decision making are presented.
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    Journal of optimization theory and applications 107 (2000), S. 89-122 
    ISSN: 1573-2878
    Keywords: optimal control ; differential games ; Euler polygonal arcs ; nonsmooth analysis ; proximal aiming ; infinitesimal decrease ; discontinuous universal near-optimal feedback
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    Topics: Mathematics
    Notes: Abstract For a general fixed-duration optimal control problem, the proximal aiming technique of nonsmooth analysis is employed in order to construct a discontinuous feedback law, whose Euler solutions are all optimal to within a prescribed tolerance, universally for all initial data in a prescribed bounded set. The technique is adapted in order to construct universal near-saddle points for two-player fixed-duration differential games of the Krasovskii–Subbotin type.
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    Journal of global optimization 16 (2000), S. 1-21 
    ISSN: 1573-2916
    Keywords: Mixed complementarity problems ; semismooth Newton method ; global optimization ; tunneling method ; filled function method
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    Topics: Mathematics
    Notes: Abstract We investigate the theoretical and numerical properties of two global optimization techniques for the solution of mixed complementarity problems. More precisely, using a standard semismooth Newton-type method as a basic solver for complementarity problems, we describe how the performance of this method can be improved by incorporating two well-known global optimization algorithms, namely a tunneling and a filled function method. These methods are tested and compared with each other on a couple of very difficult test examples.
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    Journal of optimization theory and applications 104 (2000), S. 121-133 
    ISSN: 1573-2878
    Keywords: global optimization ; simulated annealing ; convergence conditions
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    Topics: Mathematics
    Notes: Abstract In this paper, simulated annealing algorithms for continuous global optimization are considered. After a review of recent convergence results from the literature, a class of algorithms is presented for which strong convergence results can be proved without introducing assumptions which are too restrictive. The main idea of the paper is that of relating both the temperature value and the support dimension of the next candidate point, so that they are small at points with function value close to the current record and bounded away from zero otherwise.
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    Journal of optimization theory and applications 105 (2000), S. 37-54 
    ISSN: 1573-2878
    Keywords: multiple-criteria decision making ; efficient set ; global optimization ; branch-and-bound methods
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    Topics: Mathematics
    Notes: Abstract The paper presents a finite branch-and-bound variant of an outcome-based algorithm proposed by Benson and Lee for minimizing a lower-semicontinuous function over the efficient set of a bicriteria linear programming problem. Similarly to the Benson-Lee algorithm, we work primarily in the outcome space. Dissimilarly, instead of constructing a sequence of consecutive efficient edges in the outcome space, we use the idea of generating a refining sequence of partitions covering the at most two-dimensional efficient set in the outcome space. Computational experience is also presented.
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    Journal of optimization theory and applications 105 (2000), S. 477-489 
    ISSN: 1573-2878
    Keywords: optimal control ; polynomial systems ; quasilinearization ; successive approximation ; convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract It is shown in this paper that the finite-time optimal control of polynomial systems can be obtained by solving a sequence of optimal control problems for the linearized problem. The paper provides proof of convergence as well as illustration of the procedure by two examples.
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    Journal of optimization theory and applications 105 (2000), S. 543-565 
    ISSN: 1573-2878
    Keywords: stochastic games ; dynamic programming ; optimal control ; regularity theory ; Nash point
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    Topics: Mathematics
    Notes: Abstract The objective of this paper is to present a useful application of the theory of regularity of systems of nonlinear partial differential equations to the solution of stochastic differential games with N players. It is particularly interesting to notice that the structure of games fits perfectly with what is requested to prove the regularity property which is needed.
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    Journal of optimization theory and applications 104 (2000), S. 20-40 
    ISSN: 1573-2878
    Keywords: optimal control ; state constraints ; dynamic programming ; Hamilton-Jacobi equation
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    Topics: Mathematics
    Notes: Abstract In this paper, the value function for an optimal control problem with endpoint and state constraints is characterized as the unique lower semicontinuous generalized solution of the Hamilton-Jacobi equation. This is achieved under a constraint qualification (CQ) concerning the interaction of the state and dynamic constraints. The novelty of the results reported here is partly the nature of (CQ) and partly the proof techniques employed, which are based on new estimates of the distance of the set of state trajectories satisfying a state constraint from a given trajectory which violates the constraint.
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    Journal of optimization theory and applications 105 (2000), S. 347-369 
    ISSN: 1573-2878
    Keywords: random matrix products ; Lyapunov exponents ; Markov processes ; decision models ; optimal policy ; optimal control ; system spectrum
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper deals with the optimal control problem for the Lyapunov exponents of stochastic matrix products when these matrices depend on a controlled Markov process with values in a finite or countable set. Under some hypotheses, the reduced process satisfies the Doeblin condition and the existence of an optimal control is proved. Furthermore, with this optimal control, the spectrum of the system consists of only one element.
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    Journal of optimization theory and applications 105 (2000), S. 621-637 
    ISSN: 1573-2878
    Keywords: bilinear systems ; optimal control ; controllability ; stabilization ; electric power
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    Topics: Mathematics
    Notes: Abstract The purpose of this paper is an integrated overview of bilinear systems (BLS) research which has evolved over the past few decades, and a new result on control of flexible a.c. transmission systems (FACTS) is presented. BLS may be derived in many cases from principles of physics, chemistry, biology, socioeconomics, and engineering. In other cases, BLS are more accurate approximations to nonlinear systems than are traditional linear systems, as shown for example by the added bilinear terms (in state and control) for the Taylor series. While an appropriately designed linear control system may be optimum relative to some quadratic performance index without added constraints, bilinear or parametric control can be designed to improve more global performance and indeed to increase the region of attainable states. Such controllability and stabilization of BLS and of a series line-capacitor controlled FACTS is presented.
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    Journal of optimization theory and applications 107 (2000), S. 145-168 
    ISSN: 1573-2878
    Keywords: diagonal algorithms ; partitioning ; minimal description ; global optimization
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    Topics: Mathematics
    Notes: Abstract In this paper, the problem of the minimal description of the structure offunctional f(x) over an N-dimensional interval is considered. Thedescription is obtained by applying diagonal algorithms, i.e., proceduressequentially partitioning the given hyperinterval and evaluating f(x)at the vertices corresponding to the main diagonal of each generatedsubinterval. Two partition strategies traditionally used for solving thisproblem are analyzed and it is demonstrated that using them can result ina high number of redundant evaluations of the functional f(x). Anew efficient partition strategy is proposed; it reduces considerably thenumber of evaluations of f(x) and the memory complexity.
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    Nonlinear dynamics 23 (2000), S. 391-403 
    ISSN: 1573-269X
    Keywords: optimal control ; cell mapping method ; dynamic programing ; parametric control
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    Topics: Mathematics
    Notes: Abstract A strategy is proposed to solve the fixed final state optimalcontrol problem using the simple cell mapping method. A non-uniform timestep simple cell mapping is developed to create a general database fromwhich solutions of various optimal control problems can be obtained. Atwo-stage backward search algorithm is proposed to eliminate degeneratedpaths often associated with the simple cell mapping. The proposed methodcan accurately delineate the switching curves and eliminate false limitcycles in the solution. The method is applied to two optimal controlproblems with bang-bang control. The well-known minimum time controlproblem of moving a point mass from any initial condition to the originof the phase plane is studied first. This example has exact solutionsavailable which provide a yardstick to examine the accuracy of themethod. The cell size dependence of the solution accuracy is studiednumerically. The second example is a variable stiffness feedback controlproblem with tuning range saturation. The strategy proposed is able toprovide the switching curves in the phase plane. This result has notbeen obtained before.
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    Acta applicandae mathematicae 57 (1999), S. 287-338 
    ISSN: 1572-9036
    Keywords: sub-Riemannian geometry ; optimal control
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    Topics: Mathematics
    Notes: Abstract This paper is a continuation of a series of papers, dealing with contact sub-Riemannian metrics on R3. We study the special case of contact metrics that correspond to isoperimetric problems on the plane. The purpose is to understand the nature of the corresponding optimal synthesis, at least locally. It is equivalent to studying the associated sub-Riemannian spheres of small radius. It appears that the case of generic isoperimetric problems falls down in the category of generic sub-Riemannian metrics that we studied in our previous papers (although, there is a certain symmetry). Thanks to the classification of spheres, conjugate-loci and cut-loci, done in those papers, we conclude immediately. On the contrary, for the Dido problem on a 2-d Riemannian manifold (i.e. the problem of minimizing length, for a prescribed area), these results do not apply. Therefore, we study in details this special case, for which we solve the problem generically (again, for generic cases, we compute the conjugate loci, cut loci, and the shape of small sub-Riemannian spheres, with their singularities). In an addendum, we say a few words about: (1) the singularities that can appear in general for the Dido problem, and (2) the motion of particles in a nonvanishing constant magnetic field.
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    Methodology and computing in applied probability 1 (1999), S. 127-190 
    ISSN: 1387-5841
    Keywords: combinatorial optimization ; global optimization ; importance sampling ; markov chain monte carlo ; simulated annealing ; simulation
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    Topics: Mathematics
    Notes: Abstract We present a new and fast method, called the cross-entropy method, for finding the optimal solution of combinatorial and continuous nonconvex optimization problems with convex bounded domains. To find the optimal solution we solve a sequence of simple auxiliary smooth optimization problems based on Kullback-Leibler cross-entropy, importance sampling, Markov chain and Boltzmann distribution. We use importance sampling as an important ingredient for adaptive adjustment of the temperature in the Boltzmann distribution and use Kullback-Leibler cross-entropy to find the optimal solution. In fact, we use the mode of a unimodal importance sampling distribution, like the mode of beta distribution, as an estimate of the optimal solution for continuous optimization and Markov chains approach for combinatorial optimization. In the later case we show almost surely convergence of our algorithm to the optimal solution. Supporting numerical results for both continuous and combinatorial optimization problems are given as well. Our empirical studies suggest that the cross-entropy method has polynomial in the size of the problem running time complexity.
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    Mathematical methods of operations research 50 (1999), S. 121-134 
    ISSN: 1432-5217
    Keywords: Key words: Risk measurement ; global optimization ; quadratic programming ; nonlinear programming ; polynomial-approximation algorithm
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    Topics: Mathematics , Economics
    Notes: Abstract. Effective risk management requires adequate risk measurement. A basic problem herein is the quantification of market risks: what is the overall effect on a portfolio if market rates change? First, a mathematical problem statement is given and the concept of `Maximum Loss' (ML) is introduced as a method for identifying the worst case in a given set of scenarios, called `Trust Region'. Next, a technique for calculating efficiently the Maximum Loss for quadratic functions is described; the algorithm is based on the Levenberg-Marquardt theorem, which reduces the high dimensional optimization problem to a one dimensional root finding.  Following this, the idea of the `Maximum Loss Path' is presented: repetitive calculation of ML for growing trust regions leads to a sequence of worst case scenarios, which form a complete path; similarly, the path of `Maximum Profit' (MP) can be determined. Finally, all these concepts are applied to nonquadratic portfolios: so-called `Dynamic Approximations' are used to replace arbitrary profit and loss functions by a sequence of quadratic functions, which can be handled with efficient solution procedures. A description of the overall algorithm rounds off the discussion of nonlinear portfolios.
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  • 39
    ISSN: 1573-2754
    Keywords: dynamic system ; parameters identification ; optimal control ; HJB equation
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    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Mathematics , Physics
    Notes: Abstract Based on the contents of part (I) and stochastic optimal control theory, the concept of optimal control solution to parameters identification of stochastic dynamic system is discussed at first. For the completeness of the theory developed in this paper and part (I), then the procedure of establishing Hamilton-Jacobi-Bellman (HJB) equations of parameters identification problem is presented. And then, parameters identification algorithm of stochastic dynamic system is introduced. At last, an application example-local nonlinear parameters identification of dynamic system is presented.
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    Journal of optimization theory and applications 102 (1999), S. 15-36 
    ISSN: 1573-2878
    Keywords: Domain decomposition ; partial differential equations ; Riccati equation ; optimal control ; feedback law ; synthesis ; wave equation
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    Topics: Mathematics
    Notes: Abstract We present an iterative domain decomposition method for the optimal control of systems governed by linear partial differential equations. The equations can be of elliptic, parabolic, or hyperbolic type. The space region supporting the partial differential equations is decomposed and the original global optimal control problem is reduced to a sequence of similar local optimal control problems set on the subdomains. The local problems communicate through transmission conditions, which take the form of carefully chosen boundary conditions on the interfaces between the subdomains. This domain decomposition method can be combined with any suitable numerical procedure to solve the local optimal control problems. We remark that it offers a good potential for using feedback laws (synthesis) in the case of time-dependent partial differential equations. A test problem for the wave equation is solved using this combination of synthesis and domain decomposition methods. Numerical results are presented and discussed. Details on discretization and implementation can be found in Ref. 1.
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    Journal of optimization theory and applications 102 (1999), S. 299-313 
    ISSN: 1573-2878
    Keywords: Comparison of methods ; optimal control ; sensitivity ; shooting methods ; stability
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    Topics: Mathematics
    Notes: Abstract A new method for solving optimal control problems, here called multiple NOC shooting, is presented. It is developed from NOC shooting. It has some advantages over its parent and over multiple shooting, which are both successful, high-accuracy methods for optimal control. A comparison of the three methods is given, incorporating two examples.
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    Journal of optimization theory and applications 100 (1999), S. 599-622 
    ISSN: 1573-2878
    Keywords: Discrete event dynamic systems ; optimal control ; calculus of variations ; polling problems ; transportation systems ; performance optimization
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    Topics: Mathematics
    Notes: Abstract We explore an approach involving the use of calculus of variations techniques for discrete event dynamic system (DEDS) performance optimization problems. The approach is motivated by the observation that such problems can be described by separable cost functions and recursive dynamics of the same form as that used to describe conventional discrete-time continuous-variable optimal control problems. Three important difficulties are that DEDS are generally stochastic, their dynamics typically involve max and min operations, which are not everywhere differentiable, and the state variables are often discrete. We demonstrate how to overcome these difficulties by applying the approach to a transportation problem, modeled as a polling system, where we are able to derive an explicit and intuitive analytic expression for an optimal control policy.
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    Journal of optimization theory and applications 101 (1999), S. 307-328 
    ISSN: 1573-2878
    Keywords: Approximate controllability ; exact finite-dimensional controllability ; semilinear heat equation ; optimal control
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    Topics: Mathematics
    Notes: Abstract This paper deals with the approximate controllability of the semilinear heat equation, when the nonlinear term depends on both the state y and its spatial gradient ∇y and the control acts on any nonempty open subset of the domain. Our proof relies on the fact that the nonlinearity is globally Lipschitz with respect to (y, ∇y). The approximate controllability is viewed as the limit of a sequence of optimal control problems. Another key ingredient is a unique continuation property proved by Fabre (Ref. 1) in the context of linear heat equations. Finally, we prove that approximate controllability can be obtained simultaneously with exact controllability over finite-dimensional subspaces.
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    Journal of optimization theory and applications 101 (1999), S. 329-354 
    ISSN: 1573-2878
    Keywords: Algebraic Riccati equations ; parabolic equations ; optimal control
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    Topics: Mathematics
    Notes: Abstract We consider an optimal control problem with indefinite cost for an abstract model, which covers, in particular, parabolic systems in a general bounded domain. Necessary and sufficient conditions are given for the synthesis of the optimal control, which is given in terms of the Riccati operator arising from a nonstandard Riccati equation. The theory extends also a finite-dimensional frequency theorem to the infinite-dimensional setting. Applications include the heat equation with Dirichlet and Neumann controls, as well as the strongly damped Euler–Bernoulli and Kirchhoff equations with the control in various boundary conditions.
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    Journal of optimization theory and applications 101 (1999), S. 375-402 
    ISSN: 1573-2878
    Keywords: Time-optimal problems ; optimal control ; semilinear parabolic equations ; state constraints ; Pontryagin's minimum principle ; unbounded controls
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    Topics: Mathematics
    Notes: Abstract We consider time-optimal control problems for semilinear parabolic equations with pointwise state constraints and unbounded controls. A Pontryagin's principle is obtained in nonqualified form without any qualification condition. The terminal time, which is a control variable, satisfies an optimality condition, which seems to be new in the context of control problems for partial differential equations.
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    Journal of optimization theory and applications 102 (1999), S. 1-14 
    ISSN: 1573-2878
    Keywords: Partial differential equations ; optimal control ; population dynamics ; age-structured population models
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    Topics: Mathematics
    Notes: Abstract The present paper is concerned with the optimal control problem for a Gurtin–MacCamy type system describing the evolution of an age-structured population. Necessary optimality conditions are established in the form of an Euler–Lagrange system and existence of an optimal control is proved using the Ekeland principle.
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    Journal of optimization theory and applications 103 (1999), S. 1-43 
    ISSN: 1573-2878
    Keywords: DC functions ; DC programming ; global optimization ; nonconvex programming ; optimality conditions
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    Topics: Mathematics
    Notes: Abstract Mathematical programming problems dealing with functions, each of which can be represented as a difference of two convex functions, are called DC programming problems. The purpose of this overview is to discuss main theoretical results, some applications, and solution methods for this interesting and important class of programming problems. Some modifications and new results on the optimality conditions and development of algorithms are also presented.
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    Journal of optimization theory and applications 101 (1999), S. 557-580 
    ISSN: 1573-2878
    Keywords: Hybrid systems ; switching diffusions ; autonomous jumps ; impulsive jumps ; discounted cost ; optimal control
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    Notes: Abstract We address the optimal control problem of a very general stochastic hybrid system with both autonomous and impulsive jumps. The planning horizon is infinite and we use the discounted-cost criterion for performance evaluation. Under certain assumptions, we show the existence of an optimal control. We then derive the quasivariational inequalities satisfied by the value function and establish well-posedness. Finally, we prove the usual verification theorem of dynamic programming.
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    Journal of optimization theory and applications 102 (1999), S. 289-298 
    ISSN: 1573-2878
    Keywords: Concave minimization ; γ-valid cut ; Tuy cut ; global optimization
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    Topics: Mathematics
    Notes: Abstract The concept of a γ-valid cutting plane has been used in many types of algorithms for solving concave minimization problems. Unfortunately, the procedures proposed to date for constructing these cuts are valid only under certain assumptions that often may not hold in practice. Chief among these is the requirement that the feasible region of the concave minimization problem in question have full dimension, and that the objective function of this problem be concave rather than quasiconcave. In this article, we propose, validate, and show how to implement a more general γ-valid cutting plane procedure which eliminates these restrictions.
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    Discrete event dynamic systems 9 (1999), S. 241-260 
    ISSN: 1573-7594
    Keywords: flexible manufacturing ; production scheduling ; optimal control ; necessary optimality conditions
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    Topics: Mathematics
    Notes: Abstract The problem of detailed scheduling of complex flexible manufacturing systems is addressed by optimal flow control. A model problem of scheduling parallel machines is considered to obtain necessary setup conditions. Studying the conditions results in a new solution approach that takes advantage of a juggling analogy of the production/setup scheduling. This analogy is used in the paper to direct construction of a solution method. The method searches for a globally optimal schedule by means of both a juggling strategy and a method of global optimization. The results obtained for a model problem are then generalized to systems with complex production and setup operations. Computational examples demonstrate the validity of the approach.
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    Czechoslovak mathematical journal 48 (1998), S. 291-312 
    ISSN: 1572-9141
    Keywords: evolution triple ; optimal control ; monotone operator ; hemicontinuous operator ; parabolic system ; property (Q)
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    Topics: Mathematics
    Notes: Abstract We consider nonlinear systems with a priori feedback. We establish the existence of admissible pairs and then we show that the Lagrange optimal control problem admits an optimal pair. As application we work out in detail two examples of optimal control problems for nonlinear parabolic partial differential equations.
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    Journal of mathematical imaging and vision 8 (1998), S. 181-192 
    ISSN: 1573-7683
    Keywords: deterministic annealing ; global optimization ; M-estimator ; motion analysis ; robust statistics
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    Topics: Mathematics
    Notes: Abstract A robust method is presented for computing rotation angles of image sequences from a set of corresponding points containing outliers. Assuming known rotation axis, a least-squares (LS) solution are derived to compute the rotation angle from a clean data set of point correspondences. Since clean data is not guaranteed, we introduce a robust solution, based on the M-estimator, to deal with outliers. Then we present an enhanced robust algorithm, called the annealing M-estimator (AM-estimator), for reliable robust estimation. The AM-estimator has several attractive advantages over the traditional M-estimator: By definition, the AM-estimator involves neither scale estimator nor free parameters and hence avoids instabilities therein. Algorithmically, it uses a deterministic annealing technique to approximate the global solution regardless of the initialization. Experimental results are presented to compare the performance of the LS, M- and AM-estimators for the angle estimation. Experiments show that in the presence of outliers, the M-estimator outperforms the LS estimator and the AM-estimator outperforms the M-estimator.
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    Discrete event dynamic systems 8 (1998), S. 353-364 
    ISSN: 1573-7594
    Keywords: scheduling ; optimal control ; time-decomposition methods
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    Topics: Mathematics
    Notes: Abstract This paper discusses dynamic methods for solving a class of multi-project scheduling problems in which rates of job performances are controllable and resources such as money, energy or manpower per time unit, are renewable and continuously divisible. The objective is to complete the projects as close to the common due date as possible. Two different ways of imposing sequential precedence relations between project jobs are explored by formulating two dynamic models and studying their relationships on the optimal solution. Efficient time-decomposition algorithms for finding either globally optimal schedules or lower bound guided near-optimal solutions are suggested and computationally tested.
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    Discrete event dynamic systems 8 (1998), S. 175-201 
    ISSN: 1573-7594
    Keywords: hybrid systems ; optimal control ; calculus of variations ; manufacturing systems ; queueing systems ; nonsmooth optimization ; two point boundary value problems
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    Topics: Mathematics
    Notes: Abstract We propose a modeling framework for a class of hybrid systems which arise in many manufacturing environments and study related optimal control problems. In this framework, discrete entities have a state characterized by a temporal component whose evolution is described by event-driven dynamics, and a physical component whose evolution is described by time-driven dynamics. As a first step towards developing an optimal control theory for such hybrid systems, we formulate a problem consisting of a single-stage manufacturing process and use calculus of variations techniques to obtain structural properties and an explicit algorithm for deriving optimal policies.
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    Discrete event dynamic systems 8 (1998), S. 37-54 
    ISSN: 1573-7594
    Keywords: Production planning ; stochastic dynamic programming ; vanishing discount approach ; optimal control ; long-run average cost
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    Topics: Mathematics
    Notes: Abstract This paper is concerned with the problem of production planning in a flexible manufacturing system consisting of a single or parallel failure-prone machines producing a number of different products. The objective is to choose the rates of production of the various products over time in order to meet their demands at the minimum long-run average cost of production and surplus. The analysis proceeds with a study of the corresponding problem with a discounted cost. It is shown using the vanishing discount approach for the average cost problem that the Hamilton-Jacobi-Bellman equation in terms of directional derivatives has a solution consisting of the minimal average cost and the so-called potential function. The result helps in establishing a verification theorem, and in specifying an optimal control policy in terms of the potential function. The results settle a hitherto open problem as well as generalize known results.
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    Journal of optimization theory and applications 96 (1998), S. 589-626 
    ISSN: 1573-2878
    Keywords: Nonlinear control ; optimal control ; Hamilton–Jacobi–Bellman equation ; feedback synthesis ; successive approximation ; Galerkin approximation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, we develop a new method to approximate the solution to the Hamilton–Jacobi–Bellman (HJB) equation which arises in optimal control when the plant is modeled by nonlinear dynamics. The approximation is comprised of two steps. First, successive approximation is used to reduce the HJB equation to a sequence of linear partial differential equations. These equations are then approximated via the Galerkin spectral method. The resulting algorithm has several important advantages over previously reported methods. Namely, the resulting control is in feedback form and its associated region of attraction is well defined. In addition, all computations are performed off-line and the control can be made arbitrarily close to optimal. Accordingly, this paper presents a new tool for designing nonlinear control systems that adhere to a prescribed integral performance criterion.
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    Journal of optimization theory and applications 98 (1998), S. 161-173 
    ISSN: 1573-2878
    Keywords: Robust stabilization ; optimal control ; time-delay systems ; Razumikhin-type approach
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    Topics: Mathematics
    Notes: Abstract In this paper, using a Razumikhin-type approach, the stabilization of a class of uncertain nonlinear systems with time-varying delay is considered. The proposed controller is based on a specific optimal control problem. Global asymptotic stability is guaranteed for the proposed control if some algebraic condition is met. An example illustrates the use of the main result.
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    Journal of optimization theory and applications 96 (1998), S. 507-532 
    ISSN: 1573-2878
    Keywords: Rigid bodies ; Hamilton–Jacobi equation ; Riccati equation ; optimal control
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    Notes: Abstract In this paper, we consider the problem of obtaining optimal controllers which minimize a quadratic cost function for the rotational motion of a rigid body. We are not concerned with the attitude of the body and consider only the evolution of the angular velocity as described by the Euler equations. We obtain conditions which guarantee the existence of linear stabilizing optimal and suboptimal controllers. These controllers have a very simple structure.
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    Journal of optimization theory and applications 97 (1998), S. 11-28 
    ISSN: 1573-2878
    Keywords: Optimization ; nonlinear dynamic systems ; transformations ; optimal control
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    Notes: Abstract This paper deals with optimization of a class of nonlinear dynamic systems with n states and m control inputs commanded to move between two fixed states in a prescribed time. Using conventional procedures with Lagrange multipliers, it is well known that the optimal trajectory is the solution of a two-point boundary-value problem. In this paper, a new procedure for dynamic optimization is presented which relies on tools of feedback linearization to transform nonlinear dynamic systems into linear systems. In this new form, the states and controls can be written as higher derivatives of a subset of the states. Using this new form, it is possible to change constrained dynamic optimization problems into unconstrained problems. The necessary conditions for optimality are then solved efficiently using weighted residual methods.
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    Journal of optimization theory and applications 98 (1998), S. 681-700 
    ISSN: 1573-2878
    Keywords: Manufacturing systems ; bang–bang control ; dynamic programming ; optimal control
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    Notes: Abstract The system under consideration comprises n workstations in parallel and one assembly workstation. The workstations are either reliable or unreliable and the product demand is random. The n different type parts are processed first in the parallel workstations and then are joined in the assembly workstation. By minimizing the expected discounted cost, it is shown that the optimal control policy is of the bang–bang type and can be described by a set of switching manifolds. The structural properties of the optimal policy, such as monotonicity and asymptotic behavior, are investigated. These structural properties are very useful to find the optimal policy in large-size systems. Three numerical examples are given to demonstrate the results.
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    Journal of global optimization 12 (1998), S. 101-104 
    ISSN: 1573-2916
    Keywords: Increasing functional ; integral functional ; global optimization
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    Notes: Abstract In this note we introduce a suitable class of functionals, including the class of integral functionals, and prove that any (strict) local minimum of a functional of this class, defined on a decomposable space, is a (strict) global minimum. So, the recent result obtained by Giner in [1] is specified and extended.
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    Journal of optimization theory and applications 97 (1998), S. 211-227 
    ISSN: 1573-2878
    Keywords: Homotopy ; relaxation ; trajectory tracking ; global optimization ; roots ; nonlinear equations
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    Notes: Abstract Two generalized trajectory methods are combined to provide a novel and powerful numerical procedure for systematically finding multiple local extrema of a multivariable objective function. This procedure can form part of a strategy for global optimization in which the greatest local maximum and least local minimum in the interior of a specified region are compared to the largest and smallest values of the objective function on the boundary of the region. The first trajectory method, a homotopy scheme, provides a globally convergent algorithm to find a stationary point of the objective function. The second trajectory method, a relaxation scheme, starts at one stationary point and systematically connects other stationary points in the specified region by a network of trjectories. It is noted that both generalized trajectory methods actually solve the stationarity conditions, and so they can also be used to find multiple roots of a set of nonlinear equations.
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    Journal of global optimization 12 (1998), S. 61-99 
    ISSN: 1573-2916
    Keywords: Discrete Lagrangian methods ; global optimization ; satisfiability ; NP-completeness
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    Notes: Abstract Satisfiability is a class of NP-complete problems that model a wide range of real-world applications. These problems are difficult to solve because they have many local minima in their search space, often trapping greedy search methods that utilize some form of descent. In this paper, we propose a new discrete Lagrange-multiplier-based global-search method (DLM) for solving satisfiability problems. We derive new approaches for applying Lagrangian methods in discrete space, we show that an equilibrium is reached when a feasible assignment to the original problem is found and present heuristic algorithms to look for equilibrium points. Our method and analysis provides a theoretical foundation and generalization of local search schemes that optimize the objective alone and penalty-based schemes that optimize the constraints alone. In contrast to local search methods that restart from a new starting point when a search reaches a local trap, the Lagrange multipliers in DLM provide a force to lead the search out of a local minimum and move it in the direction provided by the Lagrange multipliers. In contrast to penalty-based schemes that rely only on the weights of violated constraints to escape from local minima, DLM also uses the value of an objective function (in this case the number of violated constraints) to provide further guidance. The dynamic shift in emphasis between the objective and the constraints, depending on their relative values, is the key of Lagrangian methods. One of the major advantages of DLM is that it has very few algorithmic parameters to be tuned by users. Besides the search procedure can be made deterministic and the results reproducible. We demonstrate our method by applying it to solve an extensive set of benchmark problems archived in DIMACS of Rutgers University. DLM often performs better than the best existing methods and can achieve an order-of-magnitude speed-up for some problems.
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    Journal of optimization theory and applications 97 (1998), S. 281-297 
    ISSN: 1573-2878
    Keywords: Nonlinear ship steering dynamics ; optimal control ; saturation ; slew rate limitation ; sequential gradient-restoration algorithm
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    Notes: Abstract The steering control of a ship during a course-changing maneuver is formulated as a Bolza optimal control problem, which is solved via the sequential gradient-restoration algorithm (SGRA). Nonlinear differential equations describing the yaw dynamics of a steering ship are employed as the differential constraints, and both amplitude and slew rate limits on the rudder are imposed. Two performance indices are minimized: one measures the time integral of the squared course deviation between the actual ship course and a target course; the other measures the time integral of the absolute course deviation. Numerical results indicate that a smooth transition from the initial set course to the target course is achievable, with a trade-off between the speed of response and the amount of course angle overshoot.
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    Journal of optimization theory and applications 98 (1998), S. 17-35 
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    Keywords: Multiple-objective linear programming ; vector maximization ; efficient set ; outcome set ; global optimization
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    Notes: Abstract Various difficulties arise in using decision set-based vector maximization methods to solve a multiple-objective linear programming problem (MOLP). Motivated by these difficulties, some researchers in recent years have begun to develop tools for analyzing and solving problem (MOLP) in outcome space, rather than in decision space. In this article, we present and validate a new hybrid vector maximization approach for solving problem (MOLP) in outcome space. The approach systematically integrates a simplicial partitioning technique into an outer approximation procedure to yield an algorithm that generates the set of all efficient extreme points in the outcome set of problem (MOLP) in a finite number of iterations. Some key potential practical and computational advantages of the approach are indicated.
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    Journal of optimization theory and applications 98 (1998), S. 83-108 
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    Keywords: Concave minimization ; reverse convex programs ; non-convex optimization ; global optimization ; test problems ; linear programming ; nonlinear programming ; computational experiments
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    Notes: Abstract This paper presents a method for constructing test problems with known global solutions for concave minimization under linear constraints with an additional convex constraint and for reverse convex programs with an additional convex constraint. The importance of such a construction can be realized from the fact that the well known d.c. programming problem can be formulated in this form. Then, the method is further extended to generate test problems with more than one convex constraint, tight or untight at the global solution.
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    Acta applicandae mathematicae 46 (1997), S. 29-48 
    ISSN: 1572-9036
    Keywords: Hamilton–Jacobi–Bellman equations ; nonlinear potentials ; nonlinear PDE ; viscosity solutions ; optimal control
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    Notes: Abstract A formal method of constructing the viscosity solutions for abstract nonlinear equations of Hamilton–Jacobi–Bellman (HJB) type was developed in the previous work of the author. A new advantage of this method (which was called an ‘nonlinear potentials’ method) is that it gives a possibility to choose at the first step an expected regularity of the solution and then – to construct this solution. This makes the whole procedure more simple because an analysis of regularity of viscosity solutions is usually the most complicated step. Nonlinear potentials method is a generalization of Krylov's approach to study HJB equations. In this article nonlinear potentials method is applied to elliptic degenerate HJB equations in Rd with variable coefficients.
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    Czechoslovak mathematical journal 47 (1997), S. 409-424 
    ISSN: 1572-9141
    Keywords: R δ-set ; homotopic ; contractible ; evolution triple ; evolution inclusion ; compact embedding ; optimal control
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    Notes: Abstract In the paper we study the topological structure of the solution set of a class of nonlinear evolution inclusions. First we show that it is nonempty and compact in certain function spaces and that it depends in an upper semicontinuous way on the initial condition. Then by strengthening the hypothesis on the orientor field F(t, x), we are able to show that the solution set is in fact an R δ-set. Finally some applications to infinite dimensional control systems are also presented.
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    Applied mathematics and mechanics 18 (1997), S. 61-68 
    ISSN: 1573-2754
    Keywords: viscoplastic dynamics ; optimal control ; variational principle ; finite element method
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    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Mathematics , Physics
    Notes: Abstract This paper presents the optimal control variational principle for Perzyna model which is one of the main constitutive relation of viscoplasticity in dynamics. And it could also be transformed to solve the parametric quadratic programming problem. The FEM form of this problem and its implementation have also been discussed in the paper.
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    Journal of optimization theory and applications 94 (1997), S. 487-510 
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    Keywords: Multiplicative programming ; global optimization ; concave minimization ; efficient points ; heuristic algorithms ; multiple objectives
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    Notes: Abstract Multiplicative programming problems are difficult global optimization problems known to be NP-hard. At the same time, these problems have some important applications in engineering, finance, economics, and other fields. This article has two purposes. The first is to present an analysis that shows several relationships between concave multiplicative programs and concave minimization problems, and between concave multiplicative programs and certain multiple-objective mathematical programs. The second purpose is to propose and report computational results for a heuristic efficient-point search algorithm that we have designed for use on linear multiplicative programming problems. To our knowledge, this is the first heuristic algorithm of its type. The theoretical and algorithmic results given in the article offer some potentially important new avenues for analyzing and solving multiplicative programming problems of various types.
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    Journal of optimization theory and applications 94 (1997), S. 533-560 
    ISSN: 1573-2878
    Keywords: Polynomial differential equations ; convergence of solutions ; neural network systems ; optimal control
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    Notes: Abstract We study polynomial ordinary differential systems $$\dot M(t) = QM - M(M'QM){\text{, }}M(0) = M_0 ,t \geqslant 0,$$ whereQ≥0 is an n×n matrix and M(t) is an n×k matrix. It is proven that, as t grows to infinity, the solution M(t) tends to a limit BU, where U is a k×k orthogonal matrix and B is an n×k matrix whose columns are k pairwise orthogonal, normalized eigenvectors of Q. Moreover, for almost every M 0, these eigenvectors correspond to the k maximal eigenvalues of Q; for an arbitrary Q with independent columns, we provide a procedure of computing B by employing elementary matrix operations on M 0. This result is significant for the study of certain neural network systems, and in this context it shows that M(∞) provides a principal component analyzer.
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    Journal of optimization theory and applications 94 (1997), S. 311-334 
    ISSN: 1573-2878
    Keywords: Mixed penalty method ; Frank–Wolfe method ; optimal control ; relaxed control ; lumped systems ; distributed systems
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    Notes: Abstract We consider a general optimization problem which is an abstract formulation of a broad class of state-constrained optimal control problems in relaxed form. We describe a generalized mixed Frank–Wolfe penalty method for solving the problem and prove that, under appropriate assumptions, accumulation points of sequences constructed by this method satisfy the necessary conditions for optimality. The method is then applied to relaxed optimal control problems involving lumped as well as distributed parameter systems. Numerical examples are given.
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    Journal of optimization theory and applications 94 (1997), S. 619-634 
    ISSN: 1573-2878
    Keywords: Microeconomic models ; optimal control ; linear controls ; singular subarcs ; necessary conditions ; minimum principle as LP ; direct collocation method ; indirect multiple shooting method
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    Notes: Abstract An optimal control problem with four linear controls describing a sophisticated concern model is investigated. The numerical solution of this problem by combination of a direct collocation and an indirect multiple shooting method is presented and discussed. The approximation provided by the direct method is used to estimate the switching structure caused by the four controls occurring linearly. The optimal controls have bang-bang subarcs as well as constrained and singular subarcs. The derivation of necessary conditions from optimal control theory is aimed at the subsequent application of an indirect multiple shooting method but is also interesting from a mathematical point of view. Due to the linear occurrence of the controls, the minimum principle leads to a linear programming problem. Therefore, the Karush–Kuhn–Tucker conditions can be used for an optimality check of the solution obtained by the indirect method.
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    Journal of global optimization 10 (1997), S. 37-55 
    ISSN: 1573-2916
    Keywords: global optimization ; random search ; Cauchy distributions.
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    Notes: Abstract This article presents a new algorithm, called the’’Hyperbell Algorithm‘‘, that searches for the global extrema ofnumerical functions of numerical variables. The algorithm relies on theprinciple of a monotone improving random walk whose steps aregenerated around the current position according to a gradually scaleddown Cauchy distribution. The convergence of the algorithm is provenand its rate of convergence is discussed. Its performance is tested onsome ’’hard‘‘ test functions and compared to that of other recentalgorithms and possible variants. An experimental study of complexityis also provided, and simple tuning procedures for applications areproposed.
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    Journal of global optimization 10 (1997), S. 425-437 
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    Keywords: Nonlinear 0–1 optimization ; linearization ; convex envelope ; concave extension ; bilinear programming ; global optimization
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    Notes: Abstract Convex envelopes of multilinear functions on a unit hypercube arepolyhedral. This well-known fact makes the convex envelopeapproximation very useful in the linearization of non-linear 0–1programming problems and in global bilinear optimization. This paperpresents necessary and sufficient conditions for a convex envelope to be apolyhedral function and illustrates how these conditions may be used inconstructing of convex envelopes. The main result of the paper is a simpleanalytical formula, which defines some faces of the convex envelope of amultilinear function. This formula proves to be a generalization of the wellknown convex envelope formula for multilinear monomial functions.
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    Journal of global optimization 11 (1997), S. 35-53 
    ISSN: 1573-2916
    Keywords: Molecular conformation ; global optimization ; Lennard-Jones cluster
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    Notes: Abstract This paper summarizes the current state of knowledge concerning putative global minima of the potential energy function for Lennard-Jones clusters, an intensely studied molecular conformation problem. Almost all known exceptions to global optimality of the well-known Northby multilayer icosahedral conformations for microclusters are shown to be minor variants of that geometry. The truly exceptional case of face-centered cubic lattice conformations is examined and connections are made with the macrocluster problem. Several types of algorithms and their limitations are explored, and a new variation on the growth sequence idea is presented and shown to be effective for both small and large clusters.
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    Journal of global optimization 11 (1997), S. 409-432 
    ISSN: 1573-2916
    Keywords: Location Theory ; global optimization ; discretization ; geometrical algorithms
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    Notes: Abstract Given a finite set of points in the plane anda forbidden region $$\mathcal{R}$$ , we want to find a point $$X \notin \operatorname{int} (\mathcal{R})$$ , such thatthe weighted sum to all given points is minimized.This location problem is a variant of the well-known Weber Problem, where wemeasure the distance by polyhedral gauges and alloweach of the weights to be positive ornegative. The unit ballof a polyhedral gauge may be any convex polyhedron containingthe origin. This large class of distance functions allows verygeneral (practical) settings – such as asymmetry – to be modeled. Each given point isallowed to have its own gaugeand the forbidden region $$\mathcal{R}$$ enables us to include negative information in the model. Additionallythe use of negative and positive weights allows to include thelevel of attraction or dislikeness of a new facility.Polynomial algorithms and structural properties for this globaloptimization problem (d.c. objective function and anon-convex feasible set) based on combinatorial and geometrical methodsare presented.
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    Journal of optimization theory and applications 92 (1997), S. 161-188 
    ISSN: 1573-2878
    Keywords: Production planning ; stochastic dynamic programming ; vanishing discount approach ; optimal control ; long-run average cost
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    Notes: Abstract This paper is concerned with the optimal production planning in a dynamic stochastic manufacturing system consisting of a single machine that is failure prone and facing a constant demand. The objective is to choose the rate of production over time in order to minimize the long-run average cost of production and surplus. The analysis proceeds with a study of the corresponding problem with a discounted cost. It is shown using the vanishing discount approach that the Hamilton–Jacobi–Bellman equation for the average cost problem has a solution giving rise to the minimal average cost and the so-called potential function. The result helps in establishing a verification theorem. Finally, the optimal control policy is specified in terms of the potential function.
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    Journal of optimization theory and applications 93 (1997), S. 27-51 
    ISSN: 1573-2878
    Keywords: Robust control ; multiobjective control ; optimal control ; $$\ell _1 $$ –control ; computational methods
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    Topics: Mathematics
    Notes: Abstract In this paper, we study the $$\ell _1 $$ -optimal control problem with additional constraints on the magnitude of the closed-loop frequency response. In particular, we study the case of magnitude constraints at fixed frequency points (a finite number of such constraints can be used to approximate an $$H_\infty $$ -norm constraint). In previous work, we have shown that the primal-dual formulation for this problem has no duality gap and both primal and dual problems are equivalent to convex, possibly infinite-dimensional, optimization problems with LMI constraints. Here, we study the effect of approximating the convex magnitude constraints with a finite number of linear constraints and provide a bound on the accuracy of the approximation. The resulting problems are linear programs. In the one-block case, both primal and dual programs are semi-infinite dimensional. The optimal cost can be approximated, arbitrarily well from above and within any predefined accuracy from below, by the solutions of finite-dimensional linear programs. In the multiblock case, the approximate LP problem (as well as the exact LMI problem) is infinite-dimensional in both the variables and the constraints. We show that the standard finite-dimensional approximation method, based on approximating the dual linear programming problem by sequences of finite-support problems, may fail to converge to the optimal cost of the infinite-dimensional problem.
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    Journal of optimization theory and applications 93 (1997), S. 547-556 
    ISSN: 1573-2878
    Keywords: Quadratic functionals ; quadratic equality constraints ; global optimization
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    Notes: Abstract In this paper, we investigate a constrained optimization problem with a quadratic cost functional and two quadratic equality constraints. It is assumed that the cost functional is positive definite and that the constraints are both feasible and regular (but otherwise they are unrestricted quadratic functions). Thus, the existence of a global constrained minimum is assured. We develop a necessary and sufficient condition that completely characterizes the global minimum cost. Such a condition is of essential importance in iterative numerical methods for solving the constrained minimization problem, because it readily distinguishes between local minima and global minima and thus provides a stopping criterion for the computation. The result is similar to one obtained previously by the authors. In the previous result, we gave a characterization of the global minimum of a constrained quadratic minimization problem in which the cost functional was an arbitrary quadratic functional (as opposed to positive-definite here) and the constraints were at least positive-semidefinite quadratic functions (as opposed to essentially unrestricted here).
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    Journal of optimization theory and applications 92 (1997), S. 605-631 
    ISSN: 1573-2878
    Keywords: Multiple-objective optimization ; utility function programs ; global optimization ; branch-and-bound algorithms
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    Topics: Mathematics
    Notes: Abstract Natural basic concepts in multiple-objective optimization lead to difficult multiextremal global optimization problems. Examples include detection of efficient points when nonconvexities occur, and optimization of a linear function over the efficient set in the convex (even linear) case. Assuming that a utility function exists allows one to replace in general the multiple-objective program by a single, nonconvex optimization problem, which amounts to a minimization over the efficient set when the utility function is increasing. A new algorithm is discussed for this utility function program which, under natural mild conditions, converges to an ∈-approximate global solution in a finite number of iterations. Applications include linear, convex, indefinite quadratic, Lipschitz, and d.c. objectives and constraints.
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    Journal of optimization theory and applications 95 (1997), S. 565-580 
    ISSN: 1573-2878
    Keywords: Brownian motion ; diffusion processes ; observers ; dynamic sampling ; optimal control
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    Topics: Mathematics
    Notes: Abstract Dynamic sampling utilizes the option of varying the sampling rates according to the situation of the systems, thus obtaining procedures with improved efficiencies. In this paper, the technique is applied to a typical problem in optimal control theory, that of tracking and controlling the position of an object. It is shown that the dynamic sampling results in a significantly improved procedure for this case, even when applying a suboptimal policy which can be analyzed in closed form.
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    Journal of global optimization 10 (1997), S. 185-206 
    ISSN: 1573-2916
    Keywords: global optimization ; parallel computations ; characteristicalalgorithms
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    Notes: Abstract A class of parallel characteristical algorithms for global optimization ofone-dimensional multiextremal functions is introduced. General convergence andefficiency conditions for the algorithms of the class introduced areestablished. A generalization for the multidimensional case is considered.Examples of parallel characteristical algorithms and numerical experiments arepresented.
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    Journal of global optimization 10 (1997), S. 229-256 
    ISSN: 1573-2916
    Keywords: Generalized convex multiplicative programming ; conical partition ; global optimization ; branch-and-bound.
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    Notes: Abstract We present a new method for minimizing the sum of a convex function and aproduct of k nonnegative convex functions over a convex set. This problem isreduced to a k-dimensional quasiconcave minimization problem which is solvedby a conical branch-and-bound algorithm. Comparative computational results areprovided on test problems from the literature.
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    Journal of global optimization 11 (1997), S. 91-105 
    ISSN: 1573-2916
    Keywords: Molecular conformation ; global optimization ; Lennard-Jones cluster
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    Notes: Abstract We present a new global optimization approach for solving exactly or inexactly constrained distance geometry problems. Distance geometry problems are concerned with determining spatial structures from measurements of internal distances. They arise in the structural interpretation of nuclear magnetic resonance data and in the prediction of protein structure. These problems can be naturally formulated as global optimization problems which generally are large and difficult. The global optimization method that we present is related to our previous stochastic/perturbation global optimization methods for finding minimum energy configurations, but has several key differences that are important to its success. Our computational results show that the method readily solves a set of artificial problems introduced by Moré and Wu that have up to 343 atoms. On a set of considerably more difficult protein fragment problems introduced by Hendrickson, the method solves all the problems with up to 377 atoms exactly, and finds nearly exact solution for all the remaining problems which have up to 777 atoms. These preliminary results indicate that this approach has very good promise for helping to solve distance geometry problems.
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    Journal of global optimization 11 (1997), S. 313-324 
    ISSN: 1573-2916
    Keywords: Nonconcex function ; global optimization ; genetic algorithms ; searchdirection ; Rosenbrock functions
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    Notes: Abstract In this paper, we consider the problem of minimizing a function in severalvariables which could be multimodal and may possess discontinuities. A newalgorithm for the problem based on the genetic technique is developed. Thealgorithm is hybrid in nature in the sense that it utilizes the genetictechnique to generate search directions, which are used in an optimizationscheme and is thus different from any other methods in the literature.The algorithm has been tested on the Rosenbrock valley functions in 2 and 4dimensions, and multimodal functions in 2 and 4 dimensions, which are of ahigh degree of difficulty. The results are compared with the Adaptive RandomSearch, and Simulated Annealing algorithms. The performance of the algorithmis also compared to recent global algorithms in terms of the number offunctional evaluations needed to obtain a global minimum and results show thatthe proposed algorithm is better than these algorithms on a set of standardtest problems. It seems that the proposed algorithm is efficient and robust.
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    Journal of global optimization 11 (1997), S. 341-359 
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    Keywords: Stochastic optimization ; nonlinear optimization ; global optimization ; genetic algorithm ; evolution strategy
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    Notes: Abstract A new heuristic approach for minimizing possiblynonlinear and non-differentiable continuous spacefunctions is presented. By means of an extensivetestbed it is demonstrated that the new methodconverges faster and with more certainty than manyother acclaimed global optimization methods. The newmethod requires few control variables, is robust, easyto use, and lends itself very well to parallelcomputation.
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    Journal of optimization theory and applications 95 (1997), S. 545-563 
    ISSN: 1573-2878
    Keywords: Global optimization ; real life problems ; pig liver likelihood function ; many-body potential function ; tank reactor ; optimal control
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    Notes: Abstract We describe global optimization problems from three different fields representing many-body potentials in physical chemistry, optimal control of a chemical reactor, and fitting a statistical model to empirical data. Historical background for each of the problems as well as the practical significance of the first two are given. The problems are solved by using eight recently developed stochastic global optimization algorithms representing controlled random search (4 algorithms), simulated annealing (2 algorithms), and clustering (2 algorithms). The results are discussed, and the importance of global optimization in each respective field is focused.
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    Journal of global optimization 10 (1997), S. 165-184 
    ISSN: 1573-2916
    Keywords: global optimization ; eclipsing binary stars
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    Notes: Abstract We present an algorithm for finding a global minimum of a multimodal,multivariate function whose evaluation is very expensive, affected by noise andwhose derivatives are not available. The proposed algorithm is a new version ofthe well known Price's algorithm and its distinguishing feature is that ittries to employ as much as possible the information about the objectivefunction obtained at previous iterates. The algorithm has been tested on alarge set of standard test problems and it has shown a satisfactorycomputational behaviour. The proposed algorithm has been used to solveefficiently some difficult optimization problems deriving from the study ofeclipsing binary star light curves.
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    Annals of operations research 63 (1996), S. 151-188 
    ISSN: 1572-9338
    Keywords: Tabu search ; local search ; approximate algorithms ; heuristics ; global optimization ; stochastic minimization ; hybrid algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics , Economics
    Notes: Abstract A novel algorithm for the global optimization of functions (C-RTS) is presented, in which a combinatorial optimization method cooperates with a stochastic local minimizer. The combinatorial optimization component, based on the Reactive Tabu Search recently proposed by the authors, locates the most promising “boxes”, in which starting points for the local minimizer are generated. In order to cover a wide spectrum of possible applications without user intervention, the method is designed with adaptive mechanisms: the box size is adapted to the local structure of the function to be optimized, the search parameters are adapted to obtain a proper balance of diversification and intensification. The algorithm is compared with some existing algorithms, and the experimental results are presented for a variety of benchmark tasks.
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    Mathematical notes 60 (1996), S. 383-388 
    ISSN: 1573-8876
    Keywords: optimal control ; nonlinear singular system ; state constraints ; penalty method
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    Topics: Mathematics
    Notes: Abstract A control system described by a nonlinear equation of parabolic type is considered in the situation where there may be no global solution. A particular optimal control problem subject to state constraints is studied. A proof of the existence of an optimal control is presented. The penalty method is used to obtain necessary conditions for optimal control. A proof of the convergence of this method is given. The successive approximation method is used to obtain an approximate solution for the conditions derived.
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    Journal of optimization theory and applications 88 (1996), S. 671-688 
    ISSN: 1573-2878
    Keywords: Infinite-horizon problems ; optimal control ; transversality condition ; stability ; Lyapunov exponents
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    Notes: Abstract We present necessary conditions of optimality for an infinitehorizon optimal control problem. The transversality condition is derived with the help of stability theory and is formulated in terms of the Lyapunov exponents of solutions to the adjoint equation. A problem without an exponential factor in the integral functional is considered. Necessary and sufficient conditions of optimality are proved for linear quadratic problems with conelike control constraints.
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    Journal of optimization theory and applications 91 (1996), S. 617-641 
    ISSN: 1573-2878
    Keywords: Lagrangian duality ; global optimization ; concave minimization ; penalty methods
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    Topics: Mathematics
    Notes: Abstract This paper is concerned with the global optimization problem of minimizing a concave function subject to linear constraints and an additional facial reverse convex constraint. Here, the feasible set is the union of some faces of the polyhedron determined by the linear constraints. Several well-known mathematical problems can be written or transformed into the form considered. The paper addresses the Lagrangian duality of the problem. It is shown that, under slight assumptions, the duality gap can be closed with a finite dual multiplier. Finite methods based on solving concave minimization problems are also proposed. We deal with the advantages accrued when outer approximation, cutting plane, or branch-and-bound methods are used for solving these subproblems.
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  • 94
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    Journal of global optimization 9 (1996), S. 183-216 
    ISSN: 1573-2916
    Keywords: Dynamic setups ; production and setup control ; optimal control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper deals with the optimal control of a one-machine two-product manufacturing system with setup changes, operating in a continuous time dynamic environment. The system is deterministic. When production is switched from one product to the other, a known constant setup time and a setup cost are incurred. Each product has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a feedback control problem. The objective is to minimize the total backlog, inventory and setup costs incurred over a finite horizon. The optimal solution provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady state, the optimal cyclic schedule is determined. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region, the optimal control policy is determined analytically.
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  • 95
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    Journal of optimization theory and applications 88 (1996), S. 503-539 
    ISSN: 1573-2878
    Keywords: Planar interception ; fixed end conditions ; optimal control ; singular perturbations
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A planar constant-speed interception with prescribed end conditions is analyzed. The performance index is the time of capture penalized by the control energy. For this problem, the optimal control of the pursuer is obtained in closed form, based on solving a set of nonlinear algebraic equations involving elliptic integrals. The construction of the solution is inspired by the singularly perturbed structure of the nondimensional equations of motion.
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  • 96
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    Journal of optimization theory and applications 91 (1996), S. 185-214 
    ISSN: 1573-2878
    Keywords: Gradient methods ; Liapunov direct methods ; global optimization ; stability under perturbations
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The steepest-descent technique dealing with the perturbed values of the objective function and its gradients and with nonexact line searches is considered. Attention is given to the case where the perturbations do not decrease on the algorithm trajectories; the aim is to investigate how perturbations at every iteration of the algorithm perturb its original attractor set. Based on the Liapunov direct method for attraction analysis of discrete-time processes, a sharp estimation of the attractor set generated by a perturbed steepest-descent technique with respect to the perturbation magnitudes is obtained. Some global optimization properties of finite-difference analogues of the gradient method are discovered. These properties are not inherent in methods which use exact gradients.
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  • 97
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    Journal of global optimization 8 (1996), S. 235-243 
    ISSN: 1573-2916
    Keywords: Bilevel programming problem ; nonconvex programming ; test problems ; global optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract A method of constructing test problems for linear bilevel programming problems is presented. The method selects a vertex of the feasible region, ‘far away’ from the solution of the relaxed linear programming problem, as the global solution of the bilevel problem. A predetermined number of constraints are systematically selected to be assigned to the lower problem. The proposed method requires only local vertex search and solutions to linear programs.
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  • 98
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    Journal of global optimization 9 (1996), S. 65-93 
    ISSN: 1573-2916
    Keywords: Concave minimization ; branch and bound ; simplicial subdivisions ; triangulation ; global optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this article, our primary concern is the classical problem of minimizing globally a concave function over a compact polyhedron (Problem (P)). We present a new simplicial branch and bound approach, which combines triangulations of intersections of simplices with halfspaces and ideas from outer approximation in such a way, that a class of finite algorithms for solving (P) results. For arbitrary compact convex feasible sets one obtains a not necessarily finite but convergent algorithm. Theoretical investigations include determination of the number of simplices in each applied triangulation step and bounds on the number of iterations in the resulting algorithms. Preliminary numerical results are given, and additional applications are sketched.
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  • 99
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    Journal of global optimization 8 (1996), S. 349-378 
    ISSN: 1573-2916
    Keywords: Dynamic setups ; setup and production flow control ; optimal control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper deals with the optimal scheduling of a one-machine two-product manufacturing system with setup, operating in a continuous time dynamic environment. The machine is reliable. A known constant setup time is incurred when switching over from a part to the other. Each part has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a production flow control problem. The objective is to minimize the sum of the backlog and inventory costs incurred over a finite planning horizon. The global optimal solution, expressed as an optimal feedback control law, provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady-state, the optimal cyclic schedule (Limit Cycle) is determined. This is equivalent to solving a one-machine two-product Lot Scheduling Problem. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region is associated an optimal control policy. A novel algorithm (Direction Sweeping Algorithm) is developed to obtain the optimal state trajectory (optimal policy that minimizes the sum of inventory and backlog costs) for this last case.
    Type of Medium: Electronic Resource
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  • 100
    Electronic Resource
    Electronic Resource
    Springer
    Journal of global optimization 8 (1996), S. 349-378 
    ISSN: 1573-2916
    Keywords: Dynamic setups ; setup and production flow control ; optimal control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper deals with the optimal scheduling of a one-machine two-product manufacturing system with setup, operating in a continuous time dynamic environment. The machine is reliable. A known constant setup time is incurred when switching over from a part to the other. Each part has specified constant processing time and constant demand rate, as well as an infinite supply of raw material. The problem is formulated as a production flow control problem. The objective is to minimize the sum of the backlog and inventory costs incurred over a finite planning horizon. The global optimal solution, expressed as an optimal feedback control law, provides the optimal production rate and setup switching epochs as a function of the state of the system (backlog and inventory levels). For the steady-state, the optimal cyclic schedule (Limit Cycle) is determined. This is equivalent to solving a one-machine two-product Lot Scheduling Problem. To solve the transient case, the system's state space is partitioned into mutually exclusive regions such that with each region is associated an optimal control policy. A novel algorithm (Direction Sweeping Algorithm) is developed to obtain the optimal state trajectory (optimal policy that minimizes the sum of inventory and backlog costs) for this last case.
    Type of Medium: Electronic Resource
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