Interactive Genetic Algorithms with Grey Level of Discrete Fitness
For the problem that interactive genetic algorithms lack a way of measuring the uncertainty of evaluation, a method with grey level for discrete fitness is proposed to deal with this problem. Through analyzing the grey level of discrete fitness, information reflecting the distribution of an evolutionary population is abstracted. Based on these, the adaptive probabilities of crossover and mutation operation of an evolutionary individual are proposed. The algorithm is applied to a fashion evolutionary design system, the simulation results indicate that the algorithm can effectively resolve human fatigue and improve the performance of optimization.
discrete fitness grey level interaction genetic algorithms
Guangsong Guo Shunxin Liu
School of Mechatronics Engineering Zheng Zhou Institute of Aeronautical Industry Management Zhengzhou 450015 China
国际会议
International Conference on Advances in Engineering 2011(2011年工程研究进展国际学术会议 ICAE2011)
南京
英文
798-803
2011-12-17（万方平台首次上网日期，不代表论文的发表时间）