A new method for constrained optimization problems to produce initial values

Authors:
Chao-Li Sun;Jian-Chao Zeng;Jeng-Shyang Pan
Affiliations:
Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, Shanxi, P.R. China;Complex System and Computational Intelligence Laboratory, Taiyuan University of Science and Technology, Taiyuan, Shanxi, P.R. China;Department of Electronic Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

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Abstract

To solve the hard problem that it is difficult to produce initial values satisfied with the constrained conditions in constrained optimization problems, according to the good ability of particle swarm optimization in finding good values, the paper presents a new method for producing stochastic values satisfied with constrained conditions using particle swarm optimization, which can be used in the all kinds of algorithms to produce initial values. The examples show that the algorithm this paper presents can get good stochastic values satisfied with constrained conditions.