A COMPLEX-GENETIC ALGORITHM FOR SOLVING CONSTRAINED OPTIMIZATION PROBLEMS
Constrained optimization problems(COPs) are a kind of mathematic programming problem frequently encountered in the disciplines of science and engineering application. After analyzing weaknesses of existing constrained optimization evolutionary algorithms (COEAs) , a novel improved algorithm called Complex-GA,which converts COPs into Multi-objective optimization problems(MOPs) and effectively combines Multi-objective optimization concept with global and local search, was proposed to handle COPs. Complex-GA increases the speed of optima search noticeably by combining the advantages of the two methods and overcomes the disadvantages of them.
Constrained optimization Multi-objective optimization Complez method Genetic algorithm(GA)
MING-SONG LI PU-HUA ZENG RUO-WU ZHONG HUI-PING WANG FEN-FEN ZHANG
Computing Center, Shaoguan University, Shaoguan 512005, China
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
869-873
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）