摘要
为改善遗传算法的优化性能,延长种群搜索过程,对基于进化阶段的自适应策略遗传算法进行了改进.改进的自适应策略不仅基于进化阶段,同时基于个体,特别是采用了自适应的适应值转换策略,大大降低了早熟的概率,保证算法能以较大的概率收敛到全局最优解.实验结果表明,该改进的算法确实延长了算法的搜索阶段,提高了算法的性能.
In order to improve the optimizing performance of the conventional genetic algorithm and prolong its searching process, an improvement on adaptive genetic algorithm（AGA） is made based on the evolutionary stages. In different stages the algorithm uses different adaptive strategies; at the same time different individuals use different adaptive strategies. Expecially, this algorithm uses the strategy of converting fitness to reduce probability of precociousness so as to insure that the algorithm can search global optimal solution in higher probability.
出处
《武汉大学学报（工学版）》
CAS
CSCD
北大核心
2008年第1期133-136,共4页
Engineering Journal of Wuhan University
基金
湖南省自然科学基金项目(编号:05JJ30189)
