摘要
单亲遗传算法(PGA)是一种适合于求解组合优化问题的新型算法,它与传统遗传算法相比,具有不要求初始群体具有广泛多样性,不存在“早熟收敛”问题,遗传操作简单等优点.分别从图式定理和Markov链的角度出发,对PGA的计算效率进行分析研究,提出了提高PGA计算效率的有效措施.仿真结果显示了这种算法的有效性.
Partheno-Genetie Algorithm (PGA) is a new method in solving combinatorial optimization problem.Compared with traditional genetic algorithms,the genetic operation of PGA is simpler and its initial population need not be varied and there is no immature convergence in PGA.On the basis of the schema theorem and Markov chain of PGA,the searching efficieney of PGA is analysed and an efficient measure to raise searching efficiency is pointed out.The efficiency of PGA is proved by a calculating example.
基金
国家教委博士点基金
湖南省自然科学基金
关键词
单亲遗传算法
组合优化
计算效率
Partheno-Genetic Algorithm Combinatorial Optimization Searching effieieney