摘要
利用一种多模态单亲遗传算法MPGA(MultiPartheno-GeneticalAlgorithm),目标不是发现一个最优解而是多个最优或次优解的集合。主要是对交叉算子和选择机制作了改进,群体中个体能较好地保留自己的遗传特性,增强了种群个体的分散性,使得优化结果更加全面,具有一定的可选择性。该方法不仅易实现并行或分布计算,且群体规模可以任意选取,采用的算例验证了该算法的有效性。
A MPGA(Multi-modal Partheno-Genetical Algorithm)is introduced to find not only an optimum so lution but also a set of optimal or sub-optimal solutions.Both crossover operator and selection schemes are improved so that every population individual inherits more of own genetic material to increase the diversity of population individual and to obtain overall optimized results for selection.The population size is very flexible and the computation architecture is well suited for parallel implementation.The cases adopted show its effectiveness.
出处
《电力自动化设备》
EI
CSCD
北大核心
2003年第8期65-68,共4页
Electric Power Automation Equipment