DocumentCode
2382032
Title
A novel method for solving min-max problems by using a modified particle swarm optimization
Author
Masuda, Kazuaki ; Kurihara, Kenzo ; Aiyoshi, Eitaro
Author_Institution
Fac. of Eng., Kanagawa Univ., Yokohama, Japan
fYear
2011
fDate
9-12 Oct. 2011
Firstpage
2113
Lastpage
2120
Abstract
In this paper, a method for solving min-max problems, especially for finding a solution which satisfies “min-max = max-min” condition, by using a modified particle swarm optimization (PSO) algorithm, is proposed. According to recent development in computer science, multi-point global search methods, most of which are classified into evolutionary computation and/or meta-heuristic methods, have been proposed and applied to various types of optimization problems. However, applications of them to min-max problems have been scarce despite their theoretical and practical importance. Since direct application of evolutionary computation methods to min-max problems wouldn´t work effectively, a modified PSO algorithm for solving them is proposed. The proposed method is designed: (1) to approximate the minimized and maximized functions of min-max problems by using a finite number of search points; and, (2) to obtain one of “min-max = max-min” solutions by finding the minimum of the maximized function and the maximum of the minimized function. Numerical examples demonstrate the usefulness of the proposed method.
Keywords
evolutionary computation; minimax techniques; particle swarm optimisation; evolutionary computation; max-min solution; meta-heuristic method; min-max problem; modified particle swarm optimization; multipoint global search method; Accuracy; Approximation methods; Iterative methods; Optimization; Particle swarm optimization; Vectors; Lagrange multiplier method; game theory; min-max problem; particle swarm optimization (PSO);
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics (SMC), 2011 IEEE International Conference on
Conference_Location
Anchorage, AK
ISSN
1062-922X
Print_ISBN
978-1-4577-0652-3
Type
conf
DOI
10.1109/ICSMC.2011.6083984
Filename
6083984
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