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A solution method for combined semi-infinite and semi-definite programming

Published online by Cambridge University Press:  17 February 2009

S. J. Li
Affiliation:
Department of Information and Computer Sciences, College of Sciences, Chongqing University, Chongqing, 400044, China; e-mail: lisj@cqu.edu.cn.
X. Q. Yang
Affiliation:
Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong; e-mail: mayangxq@polyu.edu.hk and mateokl@polyu.edu.hk.
K. L. Teo
Affiliation:
Department of Applied Mathematics, The Hong Kong Polytechnic University, Kowloon, Hong Kong; e-mail: mayangxq@polyu.edu.hk and mateokl@polyu.edu.hk.
S. Y. Wu
Affiliation:
Institute of Applied Mathematics, National Cheng-Kung University, Tainan 700, Taiwan; e-mail: soonyi@mail.ncku.edu.tw.
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Abstract

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In this paper, we develop a discretisation algorithm with an adaptive scheme for solving a class of combined semi-infinite and semi-definite programming problems. We show that any sequence of points generated by the algorithm contains a convergent subsequence; and furthermore, each accumulation point is a local optimal solution of the combined semi-infinite and semi-definite programming problem. To illustrate the effectiveness of the algorithm, two specific classes of problems are solved. They are relaxations of quadratically constrained semi-infinite quadratic programming problems and semi-infinite eigenvalue problems.

Information

Type
Research Article
Copyright
Copyright © Australian Mathematical Society 2004