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  • Articles  (19)
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  • Articles  (19)
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  • Springer  (19)
  • Annual Reviews
  • Blackwell Publishing Ltd
  • Elsevier
  • Periodicals Archive Online (PAO)
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  • 2005-2009
  • 1990-1994
  • 1980-1984  (19)
Year
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  • 1
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    Springer
    Mathematical programming 23 (1982), S. 326-340 
    ISSN: 1436-4646
    Keywords: Optimization ; Quasi-Newton ; Conjugate Gradient
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract In this paper we study conjugate gradient algorithms for large optimization problems. These methods accelerate (or precondition) the conjugate gradient method by means of quasi-Newton matrices, and are designed to utilize a variable amount of storage, depending on how much information is retained in the quasi-Newton matrices. We are concerned with the behaviour of such methods on the underlying quadratic model, and in particular, with finite termination properties.
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  • 2
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    Mathematical programming 20 (1981), S. 49-62 
    ISSN: 1436-4646
    Keywords: Algorithms ; Optimization ; Minimax ; Quasi-Newton ; Superlinear Convergence
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract We present an algorithm for minimax optimization that combines LP methods and quasi-Newton methods. The quasi-Newton algorithm is used only if an irregular solution is detected, in which case second-order derivative information is needed in order to obtain a fast final rate of convergence. We prove that the algorithm can converge only to a stationary point and that normally the final rate of convergence will be either quadratic or superlinear. The performance is illustrated through some numerical examples.
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  • 3
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    Mathematical programming 21 (1981), S. 172-181 
    ISSN: 1436-4646
    Keywords: Optimization ; Sparsity ; Matrix Updating
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract This paper is concerned with two questions relating to quasi-Newton updates for unconstrained optimization that exploit any sparsity present in the second derivative matrix of the objective function. First, a family of such updates is derived, that reduces to any a priori known dense update formula when no sparsity is imposed. This family uses the Frobenius projection of the desired update on the subspace of matrices that satisfy all the needed conditions. In the second part, we prove that, under mild assumptions, a positive definite sparse quasi-Newton update always exists. The proof of this result includes the explicit determination of such an update.
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  • 4
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    Mathematical programming 21 (1981), S. 331-347 
    ISSN: 1436-4646
    Keywords: Optimization ; Nonlinear Programming ; Unconstrained Optimization ; Discrete Optimal Control ; Differential Dynamic Programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract Dynamic programming techniques have proven to be more successful than alternative nonlinear programming algorithms for solving many discrete-time optimal control problems. The reason for this is that, because of the stagewise decomposition which characterizes dynamic programming, the computational burden grows approximately linearly with the numbern of decision times, whereas the burden for other methods tends to grow faster (e.g.,n 3 for Newton's method). The idea motivating the present study is that the advantages of dynamic programming can be brought to bear on classical nonlinear programming problems if only they can somehow be rephrased as optimal control problems. As shown herein, it is indeed the case that many prominent problems in the nonlinear programming literature can be viewed as optimal control problems, and for these problems, modern dynamic programming methodology is competitive with respect to processing time. The mechanism behind this success is that such methodology achieves quadratic convergence without requiring solution of large systems of linear equations.
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  • 5
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    Journal of mathematical biology 12 (1981), S. 343-354 
    ISSN: 1432-1416
    Keywords: Ecology ; Periodic differential equations ; Optimization
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Mathematics
    Notes: Summary The theory developed here applies to populations whose size x obeys a differential equation, $$\dot x = r(t)xF(x,t)$$ in which r and F are both periodic in t with period p. It is assumed that the function r, which measures a population's intrinsic rate of growth or intrinsic rate of adjustment to environmental change, is measurable and bounded with a positive lower bound. It is further assumed that the function F, which is determined by the density-dependent environmental influences on growth, is such that there is a closed interval J, with a positive lower bound, in which there lies, for each t, a number K(t) for which $$F(K(t),t) = 0$$ and, as functions on J × ℝ, F is continuous, while ∂F/∂x is continuous, negative, and bounded. Because x(t) = 0, 〉 0, or 〈 0 in accord with whether K(t) = x(t), K(t) 〉 x(t), or K(t) 〈 x(t), the number K(t) is called the “carrying capacity of the environment at time t”. The assumptions about F imply that the number K(t) is unique for each t, depends continuously and periodically on t with period P, and hence attains its extrema, K min and K max. It is, moreover, easily shown that the differential equation for x has precisely one solution x * which has its values in J and is bounded for all t in ℝ; this solution is of period p, is asymptotically stable with all of J in its domain of attraction, and is such that its minimum and maximum values, x min * and x max * , obey $$K_{min} \leqslant x_{min}^* \leqslant x_{max}^* \leqslant K_{max}^* .$$ The following question is discussed: If the function F is given, and the function r can be chosen, which choices of r come close to maximizing, x min * ? The results obtained yield a procedure for constructing, for each F and each ɛ 〉 0, a function r such that x min * 〉 K max − ɛ.
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  • 6
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    Journal of mathematical biology 16 (1982), S. 33-48 
    ISSN: 1432-1416
    Keywords: Sterile insect release ; Predation ; Stability ; Limit cycles ; Optimal control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Mathematics
    Notes: Abstract A model for the sterile insect release method of pest control in which the target species is under predatory or parasitic regulation is analyzed. The equations are nondimensionalized and the rescaled parameters are interpreted. There are four types of equilibria, whose existence and stability depend on which of ten regions of parameter space contain the rescaled parameters, and in turn give minimal release rates to achieve eradication of the pest. In at least one region, Hopf bifurcation theory shows the existence of limit cycles, but they are found to be unstable. In addition, the optimal release rate to minimize a total cost functional for pest control by the sterile release method is studied. Both approaches show that when predation accounts for a large fraction of the natural deaths, the necessary release rate and total cost are higher than for weak predation. If the predators are removed without being replaced by any other source of mortality, the cost rises in all cases but rises much more dramatically for cases with strong predation. A definite danger of the sterile release method when some predatory control exists is that the predators are frequently driven extinct before the prey, so that the target species could explode to much higher levels and be more difficult to eradicate again after the sterile release is terminated.
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  • 7
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    Journal of optimization theory and applications 33 (1981), S. 393-399 
    ISSN: 1573-2878
    Keywords: Optimal control ; nonlinear systems ; existence theorems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Let a quasilinear control system having the state space $$\bar X \subseteq R^n $$ be governed by the vector differential equation $$\dot x = G(u(t))x,$$ wherex(0) =x 0 andU is the family of all bounded measurable functions from [0,T] intoU, a compact and convex subset ofR m.LetG:U ⇑R be a bounded measurable nonlinear function, such thatG(U) is compact and convex.G −1 can be convex onG(U) or concave. The main results of the paper establish the existence of a controlu ∈U which minimizes the cost functional $$I(u) = \int_0^T {L(u(t))x(t)dt,} $$ whereL(·) is convex. A practical example of application for chemical reactions is worked out in detail.
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  • 8
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    Journal of optimization theory and applications 36 (1982), S. 495-519 
    ISSN: 1573-2878
    Keywords: Optimization ; nonlinear programming ; Numerical methods ; computational methods ; augmented Lagrangian functions
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, a new augmented Lagrangian function is introduced for solving nonlinear programming problems with inequality constraints. The relevant feature of the proposed approach is that, under suitable assumptions, it enables one to obtain the solution of the constrained problem by a single unconstrained minimization of a continuously differentiable function, so that standard unconstrained minimization techniques can be employed. Numerical examples are reported.
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  • 9
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    Journal of optimization theory and applications 38 (1982), S. 25-31 
    ISSN: 1573-2878
    Keywords: Optimization ; Kuhn-Tucker theorem ; LegendreK-transform ; equilibrium composition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The most common way of determining the steady states of a system is through the optimization of a concave function on a convex set. This applies only to cases where the objective function depends exclusively onextensive variables. In fields such as econometrics, physics, or chemistry, controllable quantities (and therefore constrained variables) are generally referred to asintensive parameters, and the states are described through a potential function. In the following pages, we examine how these two aspects can be connected.
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  • 10
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    Journal of optimization theory and applications 38 (1982), S. 153-154 
    ISSN: 1573-2878
    Keywords: Optimal control ; maximum principle ; sufficient conditions ; integro-differential equations ; path constraints ; economic applications
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Notational errors in Theorem 5.2 of Ref. 1 are corrected.
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  • 11
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    Journal of optimization theory and applications 38 (1982), S. 409-422 
    ISSN: 1573-2878
    Keywords: Optimization ; scalar optimization ; vector optimization ; optimization under vector-valued criteria ; maximum principle ; dynamic programming ; optimization of dynamic systems ; multi-criteria decision problems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The optimal control problem with vector-valued criteria is considered. A new approach to the generalization of this problem and a method of constructing the Bellman function are given.
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  • 12
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    Journal of optimization theory and applications 35 (1981), S. 535-557 
    ISSN: 1573-2878
    Keywords: Optimal control ; rotary crane ; nonlinear systems ; computational algorithms
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper is concerned with the optimal control of a rotary crane, which makes two kinds of motion (rotation and hoisting) at the same time. The optimal control which transfers a load to a desired place as fast as possible and minimizes the swing of the load during the transfer, as well as the swing at the end of transfer, is calculated on the basis of a dynamic model. A new computational technique is employed for computing the optimal control, and several numerical results are presented.
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  • 13
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    Journal of optimization theory and applications 34 (1981), S. 445-458 
    ISSN: 1573-2878
    Keywords: Optimal control ; distributed parameter systems ; nuclear reactors ; functional analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The minimum norm formalism of functional analysis is applied to the problem of minimizing a quadratic cost functional that penalizes the control effort and the deviations of the neutron flux distribution throughout the reactor core. The conditions for optimality are derived for a general, linearized, reactor model with a finite number of control rods. These conditions take the form of a coupled and finite set of Fredholm's integral equations of the second kind with nondegenerate kernels. An example is presented in which the homogeneous slab reactor model is considered. A contraction mapping algorithm is proposed to compute the optimal control.
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  • 14
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    Journal of optimization theory and applications 38 (1982), S. 241-250 
    ISSN: 1573-2878
    Keywords: Optimal control ; state constraints ; necessary conditions for optimality
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract It is shown that, when the set of necessary conditions for an optimal control problem with state-variable inequality constraints given by Bryson, Denham, and Dreyfus is appropriately augmented, it is equivalent to the (different) set of conditions given by Jacobson, Lele, and Speyer. Relationships among the various multipliers are given.
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  • 15
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    Journal of optimization theory and applications 35 (1981), S. 261-275 
    ISSN: 1573-2878
    Keywords: Optimal control ; load scheduling ; nuclear-hydro-thermal power systems
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper considers the problem of short-term optimal operation of nuclear-hydro-thermal electric power systems. The solution is obtained by use of a functional analytic optimization technique that employs the minimum norm formulation. A power system with an arbitrary number of generating stations is considered. The limited flexibility exhibited by the thermal nuclear reactors, when operating in a load-following mode, is accounted for by means of a model of the xenon concentration in their cores. The nonlinear effects induced by trapezoidal water reservoirs and the time delay of the water flow between upstream and downstream hydroplants is taken into consideration as well. A two-level iterative scheme of the feasible type is proposed for implementing the optimal solution.
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  • 16
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    Journal of optimization theory and applications 37 (1982), S. 315-341 
    ISSN: 1573-2878
    Keywords: Optimization ; unconstrained minimization ; updates ; line searches ; convergence ; numerical methods
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract We consider a certain generalization of the Huang family of updates and discuss, firstly, convergence, dependence on parameters, and descent property; secondly, invariance under nonlinear scaling, conjugacy of search directions, and possibility of achieving a better approximation of the inverse of the Hessian. The last three aspects are shown to be dependent on particular choices of parameters. A numerical experiment is presented comparing the performances of the usual and modified BFGS algorithms.
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  • 17
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    Journal of optimization theory and applications 34 (1981), S. 83-97 
    ISSN: 1573-2878
    Keywords: Optimal control ; large turboalternators ; torque control ; voltage control
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The optimal torque and voltage control for a large turbogenerator is found by using the minimum norm formulation. It should be noted that the model used is highly nonlinear. Numerical results are presented.
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  • 18
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    Journal of optimization theory and applications 38 (1982), S. 221-230 
    ISSN: 1573-2878
    Keywords: Optimal control ; dynamic programming ; singular perturbations ; system order reduction
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The singular perturbation method is used in dynamic programming to reduce the order and the computational requirements of linear systems composed of slow and fast modes. After the fast modes are separated, a near-optimum solution is computed at two different iteration rates determined by the slow and fast subsystem dynamics. The result is a reduction in the order of the computational requirement of the given system to that of the slow subsystem.
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  • 19
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    Journal of optimization theory and applications 35 (1981), S. 231-249 
    ISSN: 1573-2878
    Keywords: Optimal control ; nonconvex programming ; constrained optimization ; feasible direction methods ; dual decomposition
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, we propose a feasible-direction method for large-scale nonconvex programs, where the gradient projection on a linear subspace defined by the active constraints of the original problem is determined by dual decomposition. Results are extended for dynamical problems which include distributed delays and constraints both in state and control variables. The approach is compared with other feasible-direction approaches, and the method is applied to a power generation problem. Some computational results are included.
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