Multi-objective Genetic Algorithm based on Game Theory and its Application
Mufti-objective optimization has been a difficult problem and focus for research in fields of science and engineering.There already have a lot of classical methods for solving mufti-objective optimization problems before evolutionary algorithms were introduced in 1985.Classicalm uftiobjective optimization methods have been thor oughly developed,but there are still Lots of shortcomings in solving high dim ension,muldmodal problems.GAs can handle large space of problem and get a lot of trade-of fronts (possibl e solutions) in one evolution.A GA does not need much information about the problem before starting the optimization process,also it is not sensitive to the convex of the defined fields of the objective funetions.So using GAs in solving mufti-objective optimization problems is the mast important research direction in the future.We import knowledge of immune,co-evolution and game theory into genetic algorithm to improve the performance on solving the mufti-objective optimization problems.The results of the riments show that all of them can get better results than the original algorithm.
Multi-objective genetic algorithm Game theory application
Jian Chi Yanfei Liu
Hebei Normal University for Nationality,Department of Mathematics and Computer Chengde,China
国际会议
沈阳
英文
2341-2344
2012-09-26（万方平台首次上网日期，不代表论文的发表时间）