摘要
仿照猴群竞争产生猴王、猴王在猴群中拥有基因遗传绝对优先权的模式建立了猴王遗传算法 将种群中的点按目标函数值的大小排序 ,保留最优点和部分较优点 ,引入部分变异染色体更换部分较劣点 ,并让最优点依次与种群中的其他点进行交叉变异得到下代种群中的新点 对多种测试函数的计算表明 :猴王算法直观易懂、程序简单、参数少、计算量小 。
Monkey king Genetic Algorithm(MKGA) is proposed based on the model that monkey king emerges from the rival among monkeys and it has the first priority of genetic heredity. Points among species are arranged in the order of value of objective function.By retaining the optimum code and some better points, replacing some inferior points with mutation chromosomes, and letting the optimum code make crossover and mutation genetic algorithms with other points in the species in turn, a new code of next species is obtained. MKGA merges cross-over and mutation genetic algorithms into a single whole, and makes genetic algorithms orderly expended by making optimum code of every species as kernel. It can quickly converge to a whole optimum . Results for several continuous nonlinear programming problems show that MKGA is an effective method.
出处
《江苏大学学报(自然科学版)》
EI
CAS
2002年第4期87-90,共4页
Journal of Jiangsu University:Natural Science Edition
关键词
连续非线性规划
猴王遗传算法
遗传算法
Monkey King algorithms
genetic algorithms
nonlinear programming