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  • Articles  (64)
  • nonlinear programming  (42)
  • Optimal control  (23)
  • 1975-1979  (64)
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  • Mathematics  (64)
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  • Articles  (64)
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  • Mathematics  (64)
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  • 1
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    Journal of optimization theory and applications 15 (1975), S. 667-684 
    ISSN: 1573-2878
    Keywords: Necessary conditions ; mathematical programming ; Banach spaces ; optimization theorems ; nonlinear programming
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract In this paper, necessary optimality conditions for nonlinear programs in Banach spaces and constraint qualifications for their applicability are considered. A new optimality condition is introduced, and a constraint qualification ensuring the validity of this condition is given. When the domain space is a reflexive space, it is shown that the qualification is the weakest possible. If a certain convexity assumption is made, then this optimality condition is shown to reduce to the well-known extension of the Kuhn-Tucker conditions to Banach spaces. In this case, the constraint qualification is weaker than those previously given.
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  • 2
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    Journal of optimization theory and applications 17 (1975), S. 1-42 
    ISSN: 1573-2878
    Keywords: Optimal control ; calculus of variations ; quadratic control problems ; linear spaces ; conjugate points ; focal points ; Bolza problem ; Hilbert space techniques
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The present paper is concerned with the study of quadratic control problems on linear spaces. In particular, we are concerned with the conditions under which a quadratic criterion function is positive on certain linear spaces. This involves the elementary theory of conjugate and focal points, the existence of a conjugate system with a nonvanishing determinant, and the existence of extremal fields. The results given are in part a translation into control language of known theory for the problem of Bolza. The method used is based on the Hilbert space techniques developed earlier by the author.
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  • 3
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    Journal of optimization theory and applications 17 (1975), S. 273-278 
    ISSN: 1573-2878
    Keywords: Optimal control ; existence theorems ; control theory
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Using a recent result due to Berkovitz, we prove the existence of an optimal control in a broad class of problems, under relatively mild conditions.
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  • 4
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    Journal of optimization theory and applications 17 (1975), S. 481-491 
    ISSN: 1573-2878
    Keywords: Parameter optimization ; suboptimal control ; trajectory optimization ; Newton-Raphson methods ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract The optimal control problem is reduced to a suboptimal control problem by assuming the control histories to have particular functional forms involving a number of undetermined constants (Raleigh-Ritz method). A second-order parameter optimization method is discussed and applied to the suboptimal control problem. Also, it is shown that this approach can be used to obtain approximate Lagrange multiplier distributions for optimal control problems.
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  • 5
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    Journal of optimization theory and applications 20 (1976), S. 1-12 
    ISSN: 1573-2878
    Keywords: Methods of multipliers ; nonlinear programming ; numerical methods ; optimization theorems ; quadratically convergent algorithms
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    Topics: Mathematics
    Notes: Abstract In a recent paper (Ref. 1), the author briefly mentioned a variant of Hestenes' method of multipliers which would converge quadratically. This note examines that method in detail and provides some examples. In the quadratic-linear case, this algorithm converges in one iteration.
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  • 6
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    Journal of optimization theory and applications 20 (1976), S. 297-313 
    ISSN: 1573-2878
    Keywords: Mathematical programming ; nonlinear programming ; inequality constraints ; numerical methods ; descent methods
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    Topics: Mathematics
    Notes: Abstract This paper is concerned with first-order methods of feasible directions. Pironneau and Polak have recently proved theorems which show that three of these methods have a linear rate of convergence for certain convex problems in which the objective functions have positive definite Hessians near the solutions. In the present note, it is shown that these theorems on rate of convergence can be extended to larger classes of problems. These larger classes are determined in part by certain second-order sufficiency conditions, and they include many nonconvex problems. The arguments used here are based on the finite-dimensional version of Hestenes' indirect sufficiency method.
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  • 7
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    Journal of optimization theory and applications 21 (1977), S. 51-57 
    ISSN: 1573-2878
    Keywords: Optimal control ; linear systems ; linear-quadratic problems ; bang-bang control ; Hilbert spaces
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    Topics: Mathematics
    Notes: Abstract The control of a linear system, whose performance index is the sum of a linear term and a quadratic term, is considered. A necessary and sufficient condition is given for the optimal control to be bang-bang, and this is used to extend and clarify the results of Refs. 1–2. As an illustration, an application to an elliptic boundary-value problem is given.
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  • 8
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    Journal of optimization theory and applications 21 (1977), S. 137-174 
    ISSN: 1573-2878
    Keywords: Augmented penalty function ; method of multipliers ; penalty function methods ; nonlinear programming ; mathematical programming
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    Topics: Mathematics
    Notes: Abstract This paper describes an accelerated multiplier method for solving the general nonlinear programming problem. The algorithm poses a sequence of unconstrained optimization problems. The unconstrained problems are solved using a rank-one recursive algorithm described in an earlier paper. Multiplier estimates are obtained by minimizing the error in the Kuhn-Tucker conditions using a quadratic programming algorithm. The convergence of the sequence of unconstrained problems is accelerated by using a Newton-Raphson extrapolation process. The numerical effectiveness of the algorithm is demonstrated on a relatively large set of test problems.
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  • 9
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    Journal of optimization theory and applications 21 (1977), S. 487-504 
    ISSN: 1573-2878
    Keywords: Optimal control ; forward dynamic programming ; differential dynamic programming
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    Topics: Mathematics
    Notes: Abstract The dynamic programming formulation of the forward principle of optimality in the solution of optimal control problems results in a partial differential equation with initial boundary condition whose solution is independent of terminal cost and terminal constraints. Based on this property, two computational algorithms are described. The first-order algorithm with minimum computer storage requirements uses only integration of a system of differential equations with specified initial conditions and numerical minimization in finite-dimensional space. The second-order algorithm is based on the differential dynamic programming approach. Either of the two algorithms may be used for problems with nondifferentiable terminal cost or terminal constraints, and the solution of problems with complicated terminal conditions (e.g., with free terminal time) is greatly simplified.
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  • 10
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    Journal of optimization theory and applications 21 (1977), S. 529-530 
    ISSN: 1573-2878
    Keywords: Complementarity ; mathematical programming ; monotone maps ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract We show by an example that, in a complementarity problem where the given map is continuous and monotone on the nonnegative orthant, the existence of a feasible solution is not sufficient to guarantee existence of a solution to the complementarity problem.
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  • 11
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    Journal of optimization theory and applications 22 (1977), S. 135-194 
    ISSN: 1573-2878
    Keywords: Newton-Raphson method ; quasi-Newton method ; nonlinear programming ; multiplier method ; augmented Lagrangian method
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    Topics: Mathematics
    Notes: Abstract Two approaches to quasi-Newton methods for constrained optimization problems inR n are presented. These approaches are based on a class of Lagrange multiplier approximation formulas used by the author in his previous work on Newton's method for constrained problems. The first approach is set in the framework of a diagonalized multiplier method. From this point of view, a new update rule for the Lagrange multipliers which depends on the particular quasi-Newton method employed is given. This update rule, in contrast to most other update rules, does not require exact minimization of the intermediate unconstrained problem. In fact, the optimal convergence rate is attained in the extreme case when only one step of a quasi-Newton method is taken on this intermediate problem. The second approach transforms the constrained optimization problem into an unconstrained problem of the same dimension.
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  • 12
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    Journal of optimization theory and applications 22 (1977), S. 209-226 
    ISSN: 1573-2878
    Keywords: Mathematical programming ; nonlinear programming ; gradient methods ; feasible direction methods ; convergence
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    Topics: Mathematics
    Notes: Abstract The paper presents modifications of the generalized reduced gradient method which allows for a convergence proof. For that, a special construction of the basis is introduced, and some tools of the theory of feasible direction are used to modify the common choice of the direction at every step.
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  • 13
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    Journal of optimization theory and applications 22 (1977), S. 227-237 
    ISSN: 1573-2878
    Keywords: Mathematical programming ; nonlinear programming ; method of multipliers ; necessary conditions ; sufficient conditions
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    Topics: Mathematics
    Notes: Abstract The connection between the convergence of the Hestenes method of multipliers and the existence of augmented Lagrange multipliers for the constrained minimum problem (P): minimizef(x), subject tog(x)=0, is investigated under very general assumptions onX,f, andg. In the first part, we use the existence of augmented Lagrange multipliers as a sufficient condition for the convergence of the algorithm. In the second part, we prove that this is also a necessary condition for the convergence of the method and the boundedness of the sequence of the multiplier estimates. Further, we give very simple examples to show that the existence of augmented Lagrange multipliers is independent of smoothness condition onf andg. Finally, an application to the linear-convex problem is given.
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  • 14
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    Journal of optimization theory and applications 26 (1978), S. 243-252 
    ISSN: 1573-2878
    Keywords: Geometric programming ; duality ; subsidiary problems ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract The aim of this paper is not to derive new results, but rather to provide insight that will hopefully aid researchers involved in the design and coding of algorithms for geometric programs. The main contributions made here are: (i) a computationally useful interpretation of the Lagrange multipliers associated with the dual orthogonality constraints, (ii) a computationally useful interpretation of the Lagrange multiplier associated with the dual normality constraint, and (iii) an analysis of the much-avoided issue of subsidiary problems.
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  • 15
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    Journal of optimization theory and applications 26 (1978), S. 253-264 
    ISSN: 1573-2878
    Keywords: Geometric programs ; optimization ; generalized reduced gradient method ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract This paper describes the performance of a general-purpose GRG code for nonlinear programming in solving geometric programs. The main conclusions drawn from the experiments reported are: (i) GRG competes well with special-purpose geometric programming codes in solving geometric programs; and (ii) standard time, as defined by Colville, is an inadequate means of compensating for different computing environments while comparing optimization algorithms.
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  • 16
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    Journal of optimization theory and applications 26 (1978), S. 305-323 
    ISSN: 1573-2878
    Keywords: Optimal design ; cooling towers ; geometric programming ; posynomials ; nonlinear programming ; engineering design
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    Topics: Mathematics
    Notes: Abstract In this paper, the optimal design of dry-type natural-draft cooling towers is investigated. Using physical laws and engineering design relations that govern the system, a rather detailed optimization model is developed. This model is then reformulated as a geometric programming problem. A primary consideration in this reformulation is how certain polynomial equations may be effectively replaced by inequalities. A numerical example follows.
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  • 17
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    Journal of optimization theory and applications 26 (1978), S. 463-464 
    ISSN: 1573-2878
    Keywords: Optimal control ; queueing systems
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    Topics: Mathematics
    Notes: Abstract This comment replies to a criticism due to Klein and Gruver (Ref. 1) of our earlier paper (Ref. 2) on the application of control theory to a queueing system. The criticism concerns the state-space diagram and the table which we inadvertently gave for the terminal-reward problem, albeit incorrectly labeled, rather than for the free-endpoint problem considered in our paper. We show that the solution given by Klein and Gruver is itself incorrect and nonoptimal.
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  • 18
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    Journal of optimization theory and applications 26 (1978), S. 395-425 
    ISSN: 1573-2878
    Keywords: Optimal control ; numerical methods ; computing methods ; gradient methods ; gradient-restoration algorithms ; sequential gradient-restoration algorithms ; general boundary conditions ; nondifferential constraints ; bounded control ; bounded state
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract This paper considers the numerical solution of two classes of optimal control problems, called Problem P1 and Problem P2 for easy identification. Problem P1 involves a functionalI subject to differential constraints and general boundary conditions. It consists of finding the statex(t), the controlu(t), and the parameter π so that the functionalI is minimized, while the constraints and the boundary conditions are satisfied to a predetermined accuracy. Problem P2 extends Problem P1 to include nondifferential constraints to be satisfied everywhere along the interval of integration. Algorithms are developed for both Problem P1 and Problem P2. The approach taken is a sequence of two-phase cycles, composed of a gradient phase and a restoration phase. The gradient phase involves one iteration and is designed to decrease the value of the functional, while the constraints are satisfied to first order. The restoration phase involves one or more iterations and is designed to force constraint satisfaction to a predetermined accuracy, while the norm squared of the variations of the control, the parameter, and the missing components of the initial state is minimized. The principal property of both algorithms is that they produce a sequence of feasible suboptimal solutions: the functions obtained at the end of each cycle satisfy the constraints to a predetermined accuracy. Therefore, the values of the functionalI corresponding to any two elements of the sequence are comparable. The stepsize of the gradient phase is determined by a one-dimensional search on the augmented functionalJ, while the stepsize of the restoration phase is obtained by a one-dimensional search on the constraint errorP. The gradient stepsize and the restoration stepsize are chosen so that the restoration phase preserves the descent property of the gradient phase. Therefore, the value of the functionalI at the end of any complete gradient-restoration cycle is smaller than the value of the same functional at the beginning of that cycle. The algorithms presented here differ from those of Refs. 1 and 2, in that it is not required that the state vector be given at the initial point. Instead, the initial conditions can be absolutely general. In analogy with Refs. 1 and 2, the present algorithms are capable of handling general final conditions; therefore, they are suited for the solution of optimal control problems with general boundary conditions. Their importance lies in the fact that many optimal control problems involve initial conditions of the type considered here. Six numerical examples are presented in order to illustrate the performance of the algorithms associated with Problem P1 and Problem P2. The numerical results show the feasibility as well as the convergence characteristics of these algorithms.
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  • 19
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    Journal of optimization theory and applications 26 (1978), S. 485-500 
    ISSN: 1573-2878
    Keywords: Newton-Raphson method ; nonlinear programming ; method of multipliers ; augmented Lagrangian method
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    Topics: Mathematics
    Notes: Abstract In this study, we consider a modification of the method of multipliers of Hestenes and Powell in which the iteration is diagonalized, that is, only a fixed finite number of iterations of Newton's method are taken in the primal minimization stage. Conditions are obtained for quadratic convergence of the standard method, and it is shown that a diagonalization where two Newton steps are taken preserves the quadratic convergence for all multipler update formulas satisfying these conditions.
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  • 20
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    Journal of optimization theory and applications 26 (1978), S. 515-532 
    ISSN: 1573-2878
    Keywords: Multiplier method ; quadratic convergence ; nonlinear programming ; slack variables
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    Topics: Mathematics
    Notes: Abstract This paper presents a multiplier-type method for nonlinear programming problems with both equality and inequality constraints. Slack variables are used for the inequalities. The penalty coefficient is adjusted automatically, and the method converges quadratically to points satisfying second-order conditions.
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  • 21
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    Journal of optimization theory and applications 28 (1979), S. 1-9 
    ISSN: 1573-2878
    Keywords: Nonlinear optimization ; conjugate-gradient methods ; numerical methods ; computing methods ; mathematical programming ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract Three variants of the classical conjugate-gradient method are presented. Two of these variants are based upon a nonlinear function of a quadratic form. A restarting procedure due to Powell, and based upon some earlier work of Beale, is discussed and incorporated into two of the variants. Results of applying the four algorithms to a set of benchmark problems are included, and some tentative conclusions about the relative merits of the four schemes are presented.
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  • 22
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    Journal of optimization theory and applications 28 (1979), S. 185-212 
    ISSN: 1573-2878
    Keywords: Optimal control ; numerical methods ; computing methods ; transformation techniques ; sequential gradient-restoration algorithm ; nondifferential constraints ; state inequality constraints ; linear state inequality constraints ; partially linear state inequality constraints
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    Topics: Mathematics
    Notes: Abstract This paper considers optimal control problems involving the minimization of a functional subject to differential constraints, terminal constraints, and a state inequality constraint. The state inequality constraint is of a special type, namely, it is linear in some or all of the components of the state vector. A transformation technique is introduced, by means of which the inequality-constrained problem is converted into an equality-constrained problem involving differential constraints, terminal constraints, and a control equality constraint. The transformation technique takes advantage of the partial linearity of the state inequality constraint so as to yield a transformed problem characterized by a new state vector of minimal size. This concept is important computationally, in that the computer time per iteration increases with the square of the dimension of the state vector. In order to illustrate the advantages of the new transformation technique, several numerical examples are solved by means of the sequential gradient-restoration algorithm for optimal control problems involving nondifferential constraints. The examples show the substantial savings in computer time for convergence, which are associated with the new transformation technique.
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  • 23
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    Journal of optimization theory and applications 28 (1979), S. 303-329 
    ISSN: 1573-2878
    Keywords: Optimal control ; multiplier methods ; penalty functions ; Riccati equation ; convergence rate
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    Topics: Mathematics
    Notes: Abstract The properties of combined multiplier and penalty function methods are investigated using a second-order expansion and results known for the Riccati equation. It is shown that the lower bound of the values of the penalty constant necessary to obtain a minimum is given by a certain Riccati equation. The convergence rate of a common updating rule for the multipliers is shown to be linear.
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  • 24
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    Journal of optimization theory and applications 28 (1979), S. 391-410 
    ISSN: 1573-2878
    Keywords: Optimal control ; minimax problems ; necessary conditions ; maximum principle
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    Topics: Mathematics
    Notes: Abstract A control system x=f(t,x,u) is considered, and a cost functional ess supT 0≤t≤T 1 G(t, x(t),u(t)) is to be minimized. Necessary conditions for optimality (maximum principle and transversality conditions) are derived. It is also shown that an optimal control is optimal for the corresponding problem on a subinterval of [T 0,T 1], if a certain controllability condition is satisfied.
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  • 25
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    Journal of optimization theory and applications 29 (1979), S. 155-158 
    ISSN: 1573-2878
    Keywords: Optimal control ; queueing systems ; single-server queueing systems
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    Topics: Mathematics
    Notes: Abstract This comment is in response to a reply by Scott and Jefferson (Ref. 3) concerning the application of control theory to a queueing problem.
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  • 26
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    Journal of optimization theory and applications 29 (1979), S. 521-558 
    ISSN: 1573-2878
    Keywords: Quasi-Newton algorithm ; constrained minimization ; symmetric rank-one update ; nonlinear programming
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    Notes: Abstract We consider the problem of minimizing a differentiable function ofn parameters, with upper and lower bounds on the parameters. The motivation for this work comes from the optimization of the design of transient electrical circuits. In such optimization, the parameters are circuit elements, the bound constraints keep these parameters physically meaningful, and both the function and gradient evaluations contain errors. We describe a quasi-Newton algorithm for such problems. This algorithm handles the box constraints directly and approximates the given function locally by nonsingular quadratic functions. Numerical tests indicate that the algorithm can tolerate the errors, if the errors in the function and gradient are of the same relative size.
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  • 27
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    Journal of optimization theory and applications 29 (1979), S. 493-519 
    ISSN: 1573-2878
    Keywords: Quasi-Newton formulas ; nonlinear programming ; symmetric rank-one update
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    Notes: Abstract We consider the symmetric rank-one, quasi-Newton formula. The hereditary properties of this formula do not require quasi-Newton directions of search. Therefore, this formula is easy to use in constrained optimization algorithms; no explicit projections of either the Hessian approximations or the parameter changes are required. Moreover, the entire Hessian approximation is available at each iteration for determining the direction of search, which need not be a quasi-Newton direction. Theoretical difficulties, however, exist. Even for a positive-definite, quadratic function with no constraints, it is possible that the symmetric rank-one update may not be defined at some iteration. In this paper, we first demonstrate that such failures of definition correspond to either losses of independence in the directions of search being generated or to near-singularity of the Hessian approximation being generated. We then describe a procedure that guarantees that these updates are well-defined for any nonsingular quadratic function. This procedure has been incorporated into an algorithm for minimizing a function subject to box constraints. Box constraints arise naturally in the minimization of a function with many minima or a function that is defined only in some subregion of the space.
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  • 28
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    Journal of optimization theory and applications 29 (1979), S. 615-627 
    ISSN: 1573-2878
    Keywords: Optimal control ; advertising ; Green's theorem approach ; nearest feasible path ; infinite horizon ; optimal stationary equilibria ; economic application
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    Topics: Mathematics
    Notes: Abstract This paper considers an optimal control problem for the dynamics of a contagion model, the optimal control being the rate of advertising expenditure that maximizes the present value of net profit streams over an infinite horizon. By using a Green's theorem approach, it is shown that there are multiple optimal stationary equilibria and that the optimal path from any given initial condition is a nearest feasible path to one of these equilibria.
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  • 29
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    Journal of optimization theory and applications 16 (1975), S. 25-38 
    ISSN: 1573-2878
    Keywords: Mathematical programming ; quadratically convergent algorithms ; conjugate-direction methods ; linearly constrained nonlinear programming ; nonlinear programming
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    Notes: Abstract An iterative procedure is presented which uses conjugate directions to minimize a nonlinear function subject to linear inequality constraints. The method (i) converges to a stationary point assuming only first-order differentiability, (ii) has ann-q step superlinear or quadratic rate of convergence with stronger assumptions (n is the number of variables,q is the number of constraints which are binding at the optimum), (iii) requires the computation of only the objective function and its first derivatives, and (iv) is experimentally competitive with well-known methods.
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  • 30
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    Journal of optimization theory and applications 16 (1975), S. 207-220 
    ISSN: 1573-2878
    Keywords: Duality theory ; nonlinear programming ; mathematical programming ; convex programming ; optimization theorems
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    Topics: Mathematics
    Notes: Abstract Duality relations for the programming problem of a special class where the objective function is a sum of positive-semidefinite quadratic forms, and a sum of square roots of positive-semidefinite quadratic forms, over a convex polyhedral cone in complex space are considered. The duality relations between the primal problem and its dual are established.
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  • 31
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    Journal of optimization theory and applications 15 (1975), S. 51-67 
    ISSN: 1573-2878
    Keywords: Structural design ; plastic design ; nonlinear systems ; large displacements ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract Discrete or discretized structures are considered in the range of large displacements. Elastic plastic behavior is assumed, under the hypothesis that both yield functions and hardening rules are piecewise linear. The structural response to a single finite loading step is assumed to involve regularly progressive yielding (no local unloading). An extremum property of this structural response is established, by recognizing that the relations governing the configuration change coincide with the Kuhn-Tucker conditions of a particular nonlinear constrained optimization problem, subject to sign constraints alone. This extremum property can be regarded as an extension of the theorem of minimum potential energy. Other properties, even if computationally less attractive, broaden the theory developed, so that some results previously obtained are derived as special cases.
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  • 32
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    Journal of optimization theory and applications 18 (1976), S. 199-228 
    ISSN: 1573-2878
    Keywords: Mathematical programming ; nonlinear programming ; penalty-function methods ; convergence rate ; method of centers
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    Topics: Mathematics
    Notes: Abstract Convergence of a method of centers algorithm for solving nonlinear programming problems is considered. The algorithm is defined so that the subproblems that must be solved during its execution may be solved by finite-step procedures. Conditions are given under which the algorithm generates sequences of feasible points and constraint multiplier vectors that have accumulation points satisfying the Fritz John or the Kuhn-Tucker optimality conditions. Under stronger assumptions, linear convergence rates are established for the sequences of objective function, constraint function, feasible point, and multiplier values.
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  • 33
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    Journal of optimization theory and applications 19 (1976), S. 233-259 
    ISSN: 1573-2878
    Keywords: Geometric programming ; signomial functions ; computing methods ; nonlinear programming
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    Topics: Mathematics
    Notes: Abstract A computational comparison of several methods for dealing with polynomial geometric programs is presented. Specifically, we compare the complementary programs of Avriel and Williams (Ref. 1) with the reversed programs and the harmonic programs of Duffin and Peterson (Refs. 2, 3). These methods are used to generate a sequence of posynomial geometric programs which are solved using a dual algorithm.
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  • 34
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    Journal of optimization theory and applications 19 (1976), S. 301-325 
    ISSN: 1573-2878
    Keywords: Optimal control ; singular perturbations ; boundary-layer techniques ; two-point boundary-value problem
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    Notes: Abstract A system of equations that arises in a singularly perturbed optimal control problem is studied. We give conditions under which a formal asymptotic solution exists. This formal asymptotic solution consists of an outer expansion and left and right boundary-layer expansions. A feature of our procedure is that we do nota priori eliminate the control function from the problem. In particular, we construct a formal asymptotic expansion for the control directly. We apply our procedure to a Mayer-type problem. The paper concludes with a worked example.
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    Journal of optimization theory and applications 19 (1976), S. 455-468 
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    Keywords: Control theory ; Lagrange problems ; bounded control problems ; maximum principle ; nonlinear programming
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    Notes: Abstract In this paper, we derive necessary conditions for a measurable controlu with values in a compact convex subsetU ofR P to minimize the integral $$\int_a^b {b^0 (s,x(s),u(s))} ds$$ subject to equality and inequality state constraints. The general conditions take the form of a maximum principle which involves an integration with respect to a finitely additive set function, but conditions are given under which this reduces to the classical maximum principle. These results are similar to results derived in Ref. 1 for relaxed controls.
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    Journal of optimization theory and applications 20 (1976), S. 155-170 
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    Keywords: Unconstrained minimization ; pseudo-Newton-Raphson methods ; quasi-Newton methods ; variable-metric methods ; nonlinear programming
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    Notes: Abstract This paper surveys some of the existing approaches to quasi-Newton methods and introduces a new way for constructing inverse Hessian approximations for such algorithms. This new approach is based on restricting Newton's method to subspaces over which the inverse Hessian is assumed to be known, while expanding this subspace using gradient information. It is shown that this approach can lead to some well-known formulas for updating the inverse Hessian approximation. Deriving such updates through this approach provides new understanding of these formulas and their relation to the pseudo-Newton-Raphson algorithm.
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    Journal of optimization theory and applications 20 (1976), S. 205-213 
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    Keywords: Optimal control ; nonlinear systems ; existence theorems ; convexity
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    Notes: Abstract Let a nonlinear control system having the state space $$\underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{\bar X} \subseteq R^n $$ be governed by the vector differential equation $$\dot x\left( t \right) = f\left( {t, x\left( t \right), u\left( t \right)} \right),$$ wherex(0)=x 0 and is the family of all bounded measurable functions from [0,T] intoU, a compact and convex subset ofR m . Letg:U→R m be a bounded measurable function such thatg(U) is compact and convex, and letF be a function from $$\left[ {0, T} \right] \times \underset{\raise0.3em\hbox{$\smash{\scriptscriptstyle-}$}}{\bar X} $$ intoR n×m . If, among other conditions, fori=1, ...,n, $$f^i \left( {t, x, u_1 } \right) - f^i \left( {t, x, u_2 } \right) \leqslant F^i \left( {t, x} \right)\left( {g\left( {u_1 } \right) - g\left( {u_2 } \right)} \right),$$ whereF i is theith row ofF, then the main result of the paper establishes the existence of a control which minimizes the cost functional $$I\left( u \right) = \int {_0^T } c\left( {t, x\left( t \right), u\left( t \right)} \right)dt,$$ wherec(t,x,u) is convex inu for each (t,x). An example is worked out in detail.
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    Journal of optimization theory and applications 20 (1976), S. 171-189 
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    Keywords: Contact problems ; quadratic programming ; mechanics ; nonlinear programming ; contact stresses
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    Notes: Abstract Two-body, elastic, unbonded contact problems are formulated as quadratic programming problems. Uniqueness theorems of quadratic programming theory are applied to show that the solution of a contact problem, if one exists, is unique and can be readily found by the modified simplex method of quadratic programming. A solution technique that is compatible with finite-element methods is developed, so that contact problems with complex boundary configurations can be routinely solved. A number of classical and nonclassical problems are solved. Good agreement is found for problems with previously known solutions.
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    Journal of optimization theory and applications 20 (1976), S. 269-295 
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    Keywords: Mathematical programming ; nonlinear programming ; inequality constraints ; numerical methods ; descent methods
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    Topics: Mathematics
    Notes: Abstract The method of centers is a well-known method for solving nonlinear programming problems having inequality constraints. Pironneau and Polak have recently presented a new version of this method. In the new method, the direction of search is obtained, at each iteration, by solving a convex quadratic programming problem. This direction finding subprocedure is essentially insensitive to the dimension of the space on which the problem is defined. Moreover, the method of Pironneau and Polak is known to converge linearly for finite-dimensional convex programs for which the objective function has a positive-definite Hessian near the solution (and for which the functions involved are twice continuously differentiable). In the present paper, the method and a completely implementable version of it are shown to converge linearly for a very general class of finite-dimensional problems; the class is determined by a second-order sufficiency condition and includes both convex and nonconvex problems. The arguments employed here are based on the indirect sufficiency method of Hestenes. Furthermore, the arguments can be modified to prove linear convergence for a certain class of infinite-dimensional convex problems, thus providing an answer to a conjecture made by Pironneau and Polak.
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    Journal of optimization theory and applications 20 (1976), S. 347-357 
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    Keywords: Optimal control ; maximum principle ; corner points ; state constraints
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    Notes: Abstract This paper extends the Pontryagin maximum principle to allow for a finite number of corners, i.e., allowing for any finite number of discontinuities of the first derivatives with respect to the state variables. These corners are shown to raise the same computational difficulties caused by state constraints.
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    Journal of optimization theory and applications 20 (1976), S. 455-479 
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    Keywords: Optimal control ; numerical methods ; computing methods ; gradient methods ; quasi-Newton algorithms ; bounded control problems ; singular arcs
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    Notes: Abstract Two existing function-space quasi-Newton algorithms, the Davidon algorithm and the projected gradient algorithm, are modified so that they may handle directly control-variable inequality constraints. A third quasi-Newton-type algorithm, developed by Broyden, is extended to optimal control problems. The Broyden algorithm is further modified so that it may handle directly control-variable inequality constraints. From a computational viewpoint, dyadic operator implementation of quasi-Newton methods is shown to be superior to the integral kernel representation. The quasi-Newton methods, along with the steepest descent method and two conjugate gradient algorithms, are simulated on three relatively simple (yet representative) bounded control problems, two of which possess singular subarcs. Overall, the Broyden algorithm was found to be superior. The most notable result of the simulations was the clear superiority of the Broyden and Davidon algorithms in producing a sharp singular control subarc.
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    Journal of optimization theory and applications 21 (1977), S. 39-49 
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    Keywords: Optimal control ; augmented penalty function ; terminal constraints ; gradient methods
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    Notes: Abstract This note presents an extension of the Miele—Cragg-Iyer-Levy augmented function method for finite-dimensional optimization problems to optimal control problems. A numerical study is provided.
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    Journal of optimization theory and applications 21 (1977), S. 299-317 
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    Keywords: Aerospace engineering ; singular points ; nonlinear programming ; penalty-function methods ; variable-metric methods
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    Notes: Abstract A heuristic method is presented for determining the equilibrium states of motion of dynamic systems, in particular, spacecraft. The method can also be applied to the solution of sets of linear or nonlinear algebraic equations. A positive-semidefinite functional is formed to convert the problem to that of finding those minimum points where the functional vanishes. The process is initiated within a selecteddomain of interest by random search; convergence to a minimum is obtained by a modified Davidon's deflected gradient technique. To render this approach feasible in the presence of constraints, the functional is modified to include penalty terms which cause the functional to approach infinity at the constraint boundaries. Close approximations to solutions near the constraint boundaries are found by applying Carroll's approach in successively reducing the weighting factors of the penalty terms. After finding a minimum, the local domain around this point is eliminated by adding to the functional an interior constraint term, representing the surface under a hypersphere centered at the minimum point. The domain of consideration now becomes the subdomain formed by subtracting the space contained within this hypersphere from the previous domain of interest. Minima are now sought within the remaining space, as before.
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    Journal of optimization theory and applications 22 (1977), S. 91-101 
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    Keywords: Optimal control ; Radon measures ; existence theory ; diffusion equation
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    Notes: Abstract The existence is considered of a boundary control which drives a system governed by the one-dimensional diffusion equation from the zero state to a given final state, and at the same time minimizes a given functional. The problem is first modified to one in which the minimum is sought of a functional defined on a set of Radon measures. The existence of a minimizing measure is demonstrated, and it is shown that this measure may be approximated by a piecewise constant control. Finally, conditions are given under which a minimizing measurable control exists for the unmodified problem.
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    Journal of optimization theory and applications 22 (1977), S. 31-34 
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    Keywords: Decomposition ; nonlinear programming ; structural optimization ; trusses
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    Notes: Abstract A decomposition method, used in least-weight plastic design, is extended to solve problems with nonlinearity arising from variable structure geometry. The problem considered is that of finding vectorsx 1,x 2, andq that minimize [l max{|x 1|, |x 2|}], subject toAx 1=b 1 andAx 2=b 2, where both the vectorl and the matrixA are nonlinear functions ofq.
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    Journal of optimization theory and applications 22 (1977), S. 373-388 
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    Keywords: Optimal control ; variational inequalities ; existence theorems ; sensitivity
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    Notes: Abstract We prove an existence theorem for the optimal control of variational inequalities governed by a pseudomonotone operator: the cost is assumed to be quadratic. Then, we give an extension of the theorem to more general costs (assuming the operator to be monotone); we also give a result on a perturbation problem.
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    Journal of optimization theory and applications 22 (1977), S. 311-351 
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    Keywords: Lipschitz continuous mappings ; generalized derivatives ; nonlinear programming ; multiplier rules ; implicit mapping theorem ; inverse mapping theorem
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    Notes: Abstract In this paper, four fundamental theorems for continuously differentiable mappings (the multiplier rule for equality constraints of Carathéodory, the inverse mapping theorem, the implicit mapping theorem, and the general multiplier rule for inequality and equality constraints of Mangasarian and Fromovitz) are shown to have natural extensions valid when the mappings are only Lipschitz continuous. Involved in these extensions is a compact, convex set of linear mappings called the generalized derivative, which can be assigned to any Lipschitz continuous mapping and point of its (open) domain and which reduces to the usual derivative whenever the mapping is continuously differentiable. After a brief calculus for this generalized derivative is presented in Part I, the connection between the ranks of the linear mappings in the generalized derivative and theinteriority of the given mapping is explored in Parts II and IV; this relationship is used in Parts III and IV to prove the extensions of the theorems mentioned above.
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    Journal of optimization theory and applications 23 (1977), S. 487-510 
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    Keywords: Approximation ; multiplier methods ; nonlinear programming ; minimax problems ; Chebyshev approximation
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    Notes: Abstract In this paper, we consider a method for solving certain optimization problems with constraints, nondifferentiabilities, and other ill-conditioning terms in the cost functional by approximating them by well-behaved optimization problems. The approach is based on methods of multipliers. The convergence properties of the methods proposed can be inferred from corresponding properties of multiplier methods with partial elimination of constraints. A related analysis is provided in this paper.
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    Journal of optimization theory and applications 23 (1977), S. 563-579 
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    Keywords: Optimal control ; Green's theorem ; infinite horizon ; multiplicative problems ; optimal stationary equilibrium ; economic applications
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    Notes: Abstract Many infinite-horizon optimal control problems in management science and economics have optimal paths that approach some stationary level. Often, this path has the property of being the nearest feasible path to the stationary equilibrium. This paper obtains a simple multiplicative characterization for a single-state single-control problem to have this property. By using Green's theorem it is shown that the property is observed as long as the stationary level is sustainable by a feasible control. If not, the property is, in general, shown to be false. The paper concludes with an important theorem which states that even in the case of multiple equilibria, the optimal path is a nearest feasible path to one of them.
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    Journal of optimization theory and applications 24 (1978), S. 523-548 
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    Keywords: Multiplier method ; gradient projection method ; penalty function methods ; nonlinear programming ; parameter optimization
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    Notes: Abstract This paper describes a gradient projection-multiplier method for solving the general nonlinear programming problem. The algorithm poses a sequence of unconstrained optimization problems which are solved using a new projection-like formula to define the search directions. The unconstrained minimization of the augmented objective function determines points where the gradient of the Lagrangian function is zero. Points satisfying the constraints are located by applying an unconstrained algorithm to a penalty function. New estimates of the Lagrange multipliers and basis constraints are made at points satisfying either a Lagrangian condition or a constraint satisfaction condition. The penalty weight is increased only to prevent cycling. The numerical effectiveness of the algorithm is demonstrated on a set of test problems.
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    Journal of optimization theory and applications 25 (1978), S. 57-81 
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    Keywords: Optimal control ; nonlinear evolution equations ; reflexive Banach spaces ; existence theorems ; time-optimal control ; Bolza problem ; terminal control ; velocity field ; set-valued map ; weak Cesari property
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    Notes: Abstract The paper presents a closure theorem for the attainable trajectories of a class of control systems governed by a large class of nonlinear evolution equations in reflexive Banach spaces. Several existence theorems for optimal controls are proven that include a terminal control problem, a time-optimal control problem, and a special Bolza problem. Some results of independent interest are also presented.
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    Journal of optimization theory and applications 25 (1978), S. 229-245 
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    Keywords: Optimal control ; nonlinear large systems ; decomposition and coordination ; modification of performance index ; improvement of convergence
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    Notes: Abstract This paper proposes a coordination algorithm for multilevel control of a nonlinear dynamical system. The overall system under consideration is composed of subsystems with relatively strong interactions or relatively strong nonlinearities, or both. The objective is to minimize a performance index of quadratic type. The idea of the present algorithm is to replace the system variables associated with interactions and nonlinearities by artificially introducedinteraction variables and to decompose the overall problem into a number of smaller and simpler subproblems. At the same time, the appearance of the performance index is modified by using the interaction variables. Parameters, called weights, are introduced into the modified performance index. Choice of the values of these parameters has significant influence on the convergence rate of the algorithm, and hence is one of the major factors determining the total computing time. The interaction variables are adjusted directly by a nearly steepest-descent algorithm, without using Jacobian matrix, until the interactions attain consistency. In the paper, some sufficient conditions for convergence of the iterative algorithm are discussed in detail, and several features of the present algorithm are illustrated by examining an example.
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    Journal of optimization theory and applications 25 (1978), S. 407-414 
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    Keywords: Optimal control algorithms ; nonlinear programming ; sensitivity analysis ; switching-time location
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    Notes: Abstract A useful approach to the calculation of optimal controls is to take a piecewise constant approximation to the control and to solve the resulting nonlinear program using available techniques. There is no way of specifying the required number of control intervals a priori, but this paper shows that the adjoint system used to calculate gradients for the optimization provides at each iteration sufficient information to assess the gain from increasing the number of intervals and to indicate the best locations for the appropriate switching times. An example is presented which shows the potential computational savings that can be realized when the number of control intervals is progressively increased until the desired accuracy of the approximation is achieved.
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    Journal of optimization theory and applications 25 (1978), S. 549-554 
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    Keywords: Optimal control ; nonlinear operators ; Frechet differentiability ; Hilbert spaces ; bang-bang control
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    Notes: Abstract Necessary and sufficient conditions for the optimal control to be bang-bang are presented for a nonlinear system. The payoff, which is not necessarily quadratic, is assumed to be described by a Hilbert-space norm and to be differentiable and convex. The results are extensions of Ref. 1 to the case of nonlinear systems.
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    Journal of optimization theory and applications 25 (1978), S. 575-577 
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    Keywords: Implicit function theorem ; nonlinear programming
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    Notes: Abstract Suppose thatF:D⊂R n×Rm→Rn, withF(x 0,y 0)=0. The classical implicit function theorem requires thatF is differentiable with respect tox and moreover that ∂1 F(x 0,y 0) is nonsingular. We strengthen this theorem by removing the nonsingularity and differentiability requirements and by replacing them with a one-to-one condition onF as a function ofx.
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    Journal of optimization theory and applications 16 (1975), S. 409-428 
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    Keywords: Stability of infinite programs ; continuity of mathematical programs ; nonlinear programming ; infinitely constrained problems ; stability analysis
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    Notes: Abstract The primary concern of this paper is to investigate stability conditions for the mathematical program: findx ∈E n that maximizesf(x):g j(x)≦0 for somej ∈J, wheref is a real scalarvalued function and eachg is a real vector-valued function of possibly infinite dimension. It should be noted that we allow, possibly infinitely many, disjunctive forms. In an earlier work, Evans and Gould established stability theorems wheng is a continuous finite-dimensional real-vector function andJ=1. It is pointed out that the results of this paper reduce to the Evans-Gould results under their assumptions. Furthermore, since we use a slightly more general definition of lower and upper semicontinuous point-to-set mappings, we can dispense with the continuity ofg (except in a few instances where it is implied by convexity assumptions).
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    Journal of optimization theory and applications 26 (1978), S. 3-13 
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    Keywords: Optimality conditions ; geometric programming ; nonlinear programming ; ordinary programming ; Kuhn-Tucker conditions
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    Topics: Mathematics
    Notes: Abstract Generalizations of the Kuhn-Tucker optimality conditions are given, as are the fundamental theorems having to do with their necessity and sufficiency.
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    Journal of optimization theory and applications 27 (1979), S. 271-290 
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    Keywords: Optimal control ; boundary-value problems ; discretization ; nonlinear programming
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    Notes: Abstract A special time-optimal parabolic boundary-value control problem describing a one-dimensional heat-diffusion process is solved numerically. Using a bang-bang principle recently proved by Lempio, this problem can be transformed in such a way that the variables are jumps of bang-bang controls. A discretization is performed in two steps, and the convergence of the approximate solutions is proved. Finally, an algorithm to solve the discrete problem is developed and some numerical results are discussed.
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    Journal of optimization theory and applications 16 (1975), S. 1-24 
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    Keywords: Penalty-function methods ; mathematical programming ; nonlinear programming ; pseudo Newton-Raphson methods ; parameter optimization
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    Notes: Abstract An effective algorithm is described for solving the general constrained parameter optimization problem. The method is quasi-second-order and requires only function and gradient information. An exterior point penalty function method is used to transform the constrained problem into a sequence of unconstrained problems. The penalty weightr is chosen as a function of the pointx such that the sequence of optimization problems is computationally easy. A rank-one optimization algorithm is developed that takes advantage of the special properties of the augmented performance index. The optimization algorithm accounts for the usual difficulties associated with discontinuous second derivatives of the augmented index. Finite convergence is exhibited for a quadratic performance index with linear constraints; accelerated convergence is demonstrated for nonquadratic indices and nonlinear constraints. A computer program has been written to implement the algorithm and its performance is illustrated in fourteen test problems.
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    Journal of optimization theory and applications 15 (1975), S. 131-143 
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    Keywords: Feasible direction method ; minimum-weight design ; structural analysis ; nonlinear programming ; truss design
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    Notes: Abstract An efficient algorithm, based on Zoutendijk's feasible direction methods, is developed primarily for elastic minimum weight design of trusses subjected to stress, displacement, and cross-sectional constraints. In determining a stepsize in a usable feasible direction, an elaborate procedure is developed to gain as much weight reduction with as little computational effort as possible. A step can be taken to get more weight reduction only if the additional reduction estimated justifies the additional cost.
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    Journal of optimization theory and applications 18 (1976), S. 187-197 
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    Keywords: Least-square methods ; variable-metric methods ; gradient methods ; nonlinear programming
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    Notes: Abstract New algorithms are presented for approximating the minimum of the sum of squares ofM real and differentiable functions over anN-dimensional space. These algorithms update estimates for the location of a minimum after each one of the functions and its first derivatives are evaluated, in contrast with other least-square algorithms which evaluate allM functions and their derivatives at one point before using any of this information to make an update. These new algorithms give estimates which fluctuate about a minimum rather than converging to it. For many least-square problems, they give an adequate approximation for the solution more quickly than do other algorithms.
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    Journal of optimization theory and applications 18 (1976), S. 555-559 
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    Keywords: Optimization theorems ; global minimality ; nonconvex programming ; nonlinear programming ; mathematical programming
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    Notes: Abstract In this note, a simple proof of a theorem concerning functions whose local minima are global is presented and some closedness properties of this class of functions are discussed.
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    Journal of optimization theory and applications 26 (1978), S. 149-183 
    ISSN: 1573-2878
    Keywords: Geometric programming ; state of the art ; signomial programhing ; nonlinear programming ; software
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    Notes: Abstract This paper attempts to consolidate over 15 years of attempts at designing algorithms for geometric programming (GP) and its extensions. The pitfalls encountered when solving GP problems and some proposed remedies are discussed in detail. A comprehensive summary of published software for the solution of GP problems is included. Also included is a numerical comparison of some of the more promising recently developed computer codes for geometric programming on a specially chosen set of GP test problems. The relative performance of these codes is measured in terms of their robustness as well as speed of computation. The performance of some general nonlinear programming (NLP) codes on the same set of test problems is also given and compared with the results for the GP codes. The paper concludes with some suggestions for future research.
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    Journal of optimization theory and applications 16 (1975), S. 571-571 
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    Keywords: Newton-Raphson method ; quasilinearization method ; mathematical programming ; nonlinear programming ; quadratically convergent algorithms
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    Notes: Abstract A modification to the algorithm of Ref. 1 is given.
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