A NEW GENETIC ALGORITHM BASED ON NEGATIVE SELECTION
Genetic algorithm offers the common frame of resolving optimization problem by imitating biological evolution based on natural selection. However it has some drawbacks such as slow convergence and being premature. In genetic algorithm,individual generated by genetic operation is a bit random and even sometimes more inferior than its parents. So a new operator-negative selection that can filtrate bad-quality individual is introduced to genetic algorithm to speed up its speed of convergence and improve its global searching ability.With this new operator, a new optimization algorithm based genetic algorithm and negative selection is proposed.Furthermore this paper shows its ability to solve the function optimization problem.
Genetic algorithm immune system negative selection function optimization
NA-NA LI JUN-HUA GU BO-YING LIU
School of Electronic & Information Engineering, Tianjin University, Tianjin 300072, China;Hebei Univ Hebei University of Technology, Tianjin 300130, China
国际会议
2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)
大连
英文
4297-4299
2006-08-13（万方平台首次上网日期，不代表论文的发表时间）