NDLI: Multiobjective optimization with competitive coevolutionary genetic algorithms

Content Provider	IEEE Xplore Digital Library
Author	Liu Jianguo Wu Weiping
Copyright Year	2010
Description	Author affiliation: Department of computer, Chongqing Technology and Business University, 400067, China (Liu Jianguo) \|\| Department of Foreign Language, Chongqing Technology and Business University, 400067, China (Wu Weiping)
Abstract	Many methods solving multiobjective optimization using genetic algorithm tend to work negatively, causing that the population converges to small number of solutions due to the random genetic drift. To avoid this phenomenon, a competitive coevolutionary genetic algorithm(CoCGA) for multiobjective optimization is proposed. In the algorithms, each objective corresponds to a population. At each generation, these populations compete among themselves. The result of the competition is employed to direct the adjustment over the relation at individual and population levels. The proposed approach stores the Pareto optimal point obtained along the evolutionary process into external set. The proposed approach is validated using Schaffer's test function f2 and it is compared with the Niched Pareto GA(nPGA). Simulation experiments prove that the algorithm has a better performance in finding the Pareto solutions, and the CoCGA can have advantages over the other algorithms under consideration in convergence to the Pareto-optimal front.
Starting Page	5264
Ending Page	5267
File Size	88552
Page Count	4
File Format	PDF
ISBN	9781424462636
e-ISBN	9787894631046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-07-29
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Chinese Association of Aut
Subject Keyword	Competitive Coevolutionary Genetic Algorithm Biological system modeling Computational modeling Evolutionary computation Test Function Nickel Multiobjective Optimization Mathematical model Optimization Equations
Content Type	Text
Resource Type	Article

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