Solving Generalized Semi-Infinite Programming Problems with a Trust Region Method
نویسنده
چکیده
In this paper, a trust region method for generalized semi-infinite programming problems is presented. The method is based on [O. Yi-gui, “A filter trust region method for solving semi-infinite programming problems”, J. Appl. Math. Comput. 29, 311 (2009)]. We transformed the method from standard to generalized semi-infinite programming problems. The semismooth reformulation of the Karush–Kuhn–Tucker conditions using nonlinear complementarity functions is used. Under some standard regularity condition from semi-infinite programming, the method is convergent globally and superlinearly. Numerical examples from generalized semi-infinite programming illustrate the performance of the proposed method.
منابع مشابه
Solving Linear Semi-Infinite Programming Problems Using Recurrent Neural Networks
Linear semi-infinite programming problem is an important class of optimization problems which deals with infinite constraints. In this paper, to solve this problem, we combine a discretization method and a neural network method. By a simple discretization of the infinite constraints,we convert the linear semi-infinite programming problem into linear programming problem. Then, we use...
متن کاملA new solving approach for fuzzy multi-objective programming problem in uncertainty conditions by using semi-infinite linear programing
In practice, there are many problems which decision parameters are fuzzy numbers, and some kind of this problems are formulated as either possibilitic programming or multi-objective programming methods. In this paper, we consider a multi-objective programming problem with fuzzy data in constraints and introduce a new approach for solving these problems base on a combination of the multi-objecti...
متن کاملConvex Generalized Semi-Infinite Programming Problems with Constraint Sets: Necessary Conditions
We consider generalized semi-infinite programming problems in which the index set of the inequality constraints depends on the decision vector and all emerging functions are assumed to be convex. Considering a lower level constraint qualification, we derive a formula for estimating the subdifferential of the value function. Finally, we establish the Fritz-John necessary optimality con...
متن کاملA conceptual method for solving generalized semi-infinite programming problems via global optimization by exact discontinuous penalization
We consider a generalized semi-infinite programming problem (GSIP) with one semi-infinite constraint where the index set depends on the variable to be minimized. Keeping in mind the integral global optimization method of Zheng & Chew and its modifications we would like to outline theoretical considerations for determining coarse approximations of a solution of (GSIP) via global optimization of ...
متن کاملAn augmented Lagrangian SQP method for solving some special class of nonlinear semi–definite programming problems
In this paper, we consider a special class of nonlinear semi-definite programming problems that represents the fixed orderH 2/H∞ synthesis problem. An augmented Lagrangian sequential quadratic programming method combined with a trust region globalization strategy is described, taking advantage of the problem structure and using inexact computations. Some numerical examples that illustrate the p...
متن کامل