𝔖 Bobbio Scriptorium
✦   LIBER   ✦

A dual parameterization algorithm for linear quadratic semi-infinite programming problems

✍ Scribed by Y. Liu; K.L. Teo

Publisher
Elsevier Science
Year
2001
Tongue
English
Weight
461 KB
Volume
47
Category
Article
ISSN
0362-546X

No coin nor oath required. For personal study only.

✦ Synopsis

In this paper, we consider a class of (\mathrm{LQ}) semi-infinite programming (SIP) problems where the objective function is positive quadratic and the linear infinite constraint functions continuously depend on its index variable on a compact set. By using the dual parameterization technique, this SIP problem can be reduced to a finite nonlinear programming problem with special features. It is known that a global solution of the nonlinear problem will give rise to the solution of the SIP problem. The aim of this paper is to develop a global solution method for the nonlinear programming problem.

πŸ“œ SIMILAR VOLUMES

A globally convergent method for semi-in
A globally convergent method for semi-infinite linear programming
✍ H. Hu πŸ“‚ Article πŸ“… 1996 πŸ› Springer US 🌐 English βš– 541 KB

This paper presents a globally convergent method for solving a general semi-infinite linear programming problem. Some important features of this method include: It can solve a semi-infinite linear program having an unbounded feasible region. It requires an inexact solution to a nonlinear subproblem

Optimality conditions for convex semi-in
Optimality conditions for convex semi-infinite programming problems
✍ A. Ben-Tal; L. Kerzner; S. Zlobec πŸ“‚ Article πŸ“… 1980 πŸ› John Wiley and Sons 🌐 English βš– 923 KB

## Abstract This paper gives characterization of optimal Solutions for convex semiinfinite programming problems. These characterizations are free of a constraint qualification assumption. Thus they overcome the deficiencies of the semiinfinite versions of the Fritz John and the Kuhn‐Tucker theories