共查询到20条相似文献,搜索用时 156 毫秒
1.
R. Reemtsen 《Journal of Optimization Theory and Applications》1991,71(1):85-103
In the first part of this paper, we prove the convergence of a class of discretization methods for the solution of nonlinear semi-infinite programming problems, which includes known methods for linear problems as special cases. In the second part, we modify and study this type of algorithms for linear problems and suggest a specific method which requires the solution of a quadratic programming problem at each iteration. With this algorithm, satisfactory results can also be obtained for a number of singular problems. We demonstrate the performance of the algorithm by several numerical examples of multivariate Chebyshev approximation problems. 相似文献
2.
The so called dual parameterization method for quadratic semi-infinite programming (SIP) problems is developed recently. A dual parameterization algorithm is also proposed for numerical solution of such problems. In this paper, we present and improved adaptive algorithm for quadratic SIP problems with positive definite objective and multiple linear infinite constraints. In each iteration of the new algorithm, only a quadratic programming problem with a limited dimension and a limited number of constraints is required to be solved. Furthermore, convergence result is given. The efficiency of the new algorithm is shown by solving a number of numerical examples. 相似文献
3.
In the sequel of the work reported in Liu et al. (1999), in which a method based on a dual parametrization is used to solve
linear-quadratic semi-infinite programming (SIP) problems, a sequential quadratic programming technique is proposed to solve
nonlinear SIP problems. A merit function to measure progress toward the solution and a procedure to compute the penalty parameter
are also proposed. 相似文献
4.
K. C. Kiwiel 《Journal of Optimization Theory and Applications》1987,55(2):271-287
We consider the problem of minimizing a nondifferentiable function that is the pointwise maximum over a compact family of continuously differentiable functions. We suppose that a certain convex approximation to the objective function can be evaluated. An iterative method is given which uses as successive search directions approximate solutions of semi-infinite quadratic programming problems calculated via a new generalized proximity algorithm. Inexact line searches ensure global convergence of the method to stationary points.This work was supported by Project No. CPBP-02.15/2.1.1. 相似文献
5.
We formulate convex semi-infinite programming problems in a functional analytic setting and derive optimality conditions and several duality results, based on which we develop a computational framework for solving convex semi-infinite programs. 相似文献
6.
7.
We present in this paper a numerical method for solving non-strictly-convex quadratic semi-infinite programming including linear semi-infinite programming. The proposed method transforms the problem into a series of strictly convex quadratic semi-infinite programming problems. Several convergence results and a numerical experiment are given. 相似文献
8.
C. Ling L. Q. Qi G. L. Zhou S. Y. Wu 《Journal of Optimization Theory and Applications》2006,129(1):147-164
The semi-infinite programming (SIP) problem is a program with infinitely many constraints. It can be reformulated as a nonsmooth
nonlinear programming problem with finite constraints by using an integral function. Due to the nondifferentiability of the
integral function, gradient-based algorithms cannot be used to solve this nonsmooth nonlinear programming problem. To overcome
this difficulty, we present a robust smoothing sequential quadratic programming (SQP) algorithm for solving the nonsmooth
nonlinear programming problem. At each iteration of the algorthm, we need to solve only a quadratic program that is always
feasible and solvable. The global convergence of the algorithm is established under mild conditions. Numerical results are
given.
Communicated by F. Giannessi
His work was supported by the Hong Kong Research Grant Council
His work was supported by the Australian Research Council. 相似文献
9.
This paper develops a wholly linear formulation of the posynomial geometric programming problem. It is shown that the primal geometric programming problem is equivalent to a semi-infinite linear program, and the dual problem is equivalent to a generalized linear program. Furthermore, the duality results that are available for the traditionally defined primal-dual pair are readily obtained from the duality theory for semi-infinite linear programs. It is also shown that two efficient algorithms (one primal based and the other dual based) for geometric programming actually operate on the semi-infinite linear program and its dual. 相似文献
10.
11.
Liu Y. Ito S. Lee H. W. J. Teo K. L. 《Journal of Optimization Theory and Applications》2001,108(3):617-632
Consider the class of linear-quadratic (LQ) optimal control problems with continuous linear state constraints, that is, constraints imposed on every instant of the time horizon. This class of problems is known to be difficult to solve numerically. In this paper, a computational method based on a semi-infinite programming approach is given. The LQ optimal control problem is formulated as a positive-quadratic infinite programming problem. This can be done by considering the control as the decision variable, while taking the state as a function of the control. After parametrizing the decision variable, an approximate quadratic semi-infinite programming problem is obtained. It is shown that, as we refine the parametrization, the solution sequence of the approximate problems converges to the solution of the infinite programming problem (hence, to the solution of the original optimal control problem). Numerically, the semi-infinite programming problems obtained above can be solved efficiently using an algorithm based on a dual parametrization method. 相似文献
12.
本文利用一个精确增广Lagrange函数研究了一类广义半无限极小极大规划问题。在一定的条件下将其转化为标准的半无限极小极大规划问题。研究了这两类问题的最优解和最优值之间的关系,利用这种关系和标准半无限极小极大规划问题的一阶最优性条件给出了这类广义半无限极小极大规划问题的一个新的一阶最优性条件。 相似文献
13.
《Optimization》2012,61(6):713-726
We describe a reduction algorithm for solving semi-infinite programming problems. The proposed algorithm uses the simulated annealing method equipped with a function stretching as a multi-local procedure, and a penalty technique for the finite optimization process. An exponential penalty merit function is reduced along each search direction to ensure convergence from any starting point. Our preliminary numerical results seem to show that the algorithm is very promising in practice. 相似文献
14.
半局部凸多目标半无限规划的最优性 总被引:1,自引:1,他引:0
张蕾蕾 《数学的实践与认识》2008,38(16)
研究半局部凸函数在多目标半无限规划下的最优性.利用半局部凸函数,讨论了在多目标半无限规划下的择一定理,最优性条件.使半局部凸函数运用的范围更加广泛. 相似文献
15.
K.O. Kortanek 《Optimization》2016,65(4):707-727
Motivated by a recent Basu–Martin–Ryan paper, we obtain a reduced primal-dual pair of a linear semi-infinite programming problem by applying an amended Fourier–Motzkin elimination method to the linear semi-infinite inequality system. The reduced primal-dual pair is equivalent to the original one in terms of consistency, optimal values and asymptotic consistency. Working with this reduced pair and reformulating a linear semi-infinite programme as a linear programme over a convex cone, we reproduce all the theorems that lead to the full eleven possible duality state classification theory. Establishing classification results with the Fourier–Motzkin method means that the two classification theorems for linear semi-infinite programming, 1969 and 1974, have been proved by new and exciting methods. We also show in this paper that the approach to study linear semi-infinite programming using Fourier–Motzkin elimination is not purely algebraic, it is mixed algebraic-analysis. 相似文献
16.
The development of efficient algorithms that provide all the local minima of a function is crucial to solve certain subproblems
in many optimization methods. A “multi-local” optimization procedure using inexact line searches is presented, and numerical
experiments are also reported. An application of the method to a semi-infinite programming procedure is included.
This work was partially supported by Ministerio de Educación y Ciencia, Spain, DGICYT grant PB93-0703. Author (*) was supported
by the Consellería d'Educació i Ciència of the Generalitat Valenciana. 相似文献
17.
18.
K. H. Meyn 《Journal of Optimization Theory and Applications》1981,34(3):355-369
We investigate a method for approximating a convex domainCR
n described by a (possibly infinite) set of linear inequalities. In contrast to other methods, the approximating domains (polyhedrons) lie insideC. We discuss applications to semi-infinite programming and present numerical examples.The paper was written at the Institut für Angewandte Mathematik, Universität Hamburg, Hamburg, West Germany. The author thanks Prof. U. Eckhardt, Dr. K. Roleff, and Prof. B. Werner for helpful discussions. 相似文献
19.
In this paper, the classical KKT, complementarity and Lagrangian saddle-point conditions are generalized to obtain equivalent conditions characterizing the optimality of a feasible solution to a general linear semi-infinite programming problem without constraint qualifications. The method of this paper differs from the usual convex analysis methods and its main idea is rooted in some fundamental properties of linear programming. 相似文献
20.
In contrast to stochastic differential equation models used for the calculation of the term structure of interest rates, we
develop an approach based on linear dynamical systems under non-stochastic uncertainty with perturbations. The uncertainty
is described in terms of known feasible sets of varying parameters. Observations are used in order to estimate these parameters
by minimizing the maximum of the absolute value of measurement errors, which leads to a linear or nonlinear semi-infinite
programming problem. A regularized logarithmic barrier method for solving (ill-posed) convex semi-infinite programming problems
is suggested. In this method a multi-step proximal regularization is coupled with an adaptive discretization strategy in the
framework of an interior point approach. A special deleting rule permits one to use only a part of the constraints of the
discretized problems. Convergence of the method and its stability with respect to data perturbations in the cone of convexC
1-functions are studied. On the basis of the solutions of the semi-infinite programming problems a technical trading system
for future contracts of the German DAX is suggested and developed.
Supported by the Stiftung Rheinland/Pfalz für Innovation, No. 8312-386261/307. 相似文献