DocumentCode
2526097
Title
A Game Model Based Co-evolutionary Algorithms for Multiobjective Optimization Problems
Author
Wang, Gaoping ; Wang, Yongji
Volume
3
fYear
2006
fDate
Aug. 30 2006-Sept. 1 2006
Firstpage
312
Lastpage
315
Abstract
In this paper, we discuss multiobjective optimization problems solved by co-evolutionary algorithms. We present a game model based co-evolutionary algorithm (GMBCA) to solve this class of problems and its performance is analyzed in comparing its results with those obtained with four others algorithms. Finally, the GMBCA is applied to solve the nutrition decision making problem to map the Pareto-optimum front. The results in the problem show its effectiveness
Keywords
decision making; evolutionary computation; game theory; optimisation; Pareto-optimum front; coevolutionary algorithm; game model; multiobjective optimization problem; nutrition decision making problem; Algorithm design and analysis; Constraint optimization; Control engineering; Cost function; Decision making; Evolutionary computation; Game theory; Genetic algorithms; Information science; Performance analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Innovative Computing, Information and Control, 2006. ICICIC '06. First International Conference on
Conference_Location
Beijing
Print_ISBN
0-7695-2616-0
Type
conf
DOI
10.1109/ICICIC.2006.382
Filename
1692177
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