Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/34360
Title: An adaptive dual parametrization algorithm for quadratic semi-infinite programming problems
Authors: Liu, Y
Teo, K
Keywords: Semi-infinite programming
Global optimization
Dual parametrization
Adaptive algorithm
Convergence
Issue Date: 2002
Publisher: Kluwer Academic Publ
Source: Journal of global optimization, 2002, v. 24, no. 2, p. 205-217 How to cite?
Journal: Journal of global optimization 
Abstract: The so called dual parametrization method for quadratic semi-infinite programming (SIP) problems is developed recently for quadratic SIP problems with a single infinite constraint. A dual parametrization algorithm is also proposed for numerical solution of such problems. In this paper, we consider quadratic SIP problems with positive definite objective and multiple linear infinite constraints. All the infinite constraints are supposed to be continuously dependent on their index variable on a compact set which is defined by a number equality and inequalities. We prove that in the multiple infinite constraint case, the minimu parametrization number, just as in the single infinite constraint case, is less or equal to the dimension of the SIP problem. Furthermore, we propose an adaptive dual parametrization algorithm with convergence result. Compared with the previous dual parametrization algorithm, the adaptive algorithm solves subproblems with much smaller number of constraints. The efficiency of the new algorithm is shown by solving a number of numerical examples.
URI: http://hdl.handle.net/10397/34360
ISSN: 0925-5001
EISSN: 1573-2916
DOI: 10.1023/A:1020234019886
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