遗传算法中自适应的比例选择策略  

Self-adaptive proportional selection strategy for genetic algorithm

作　　者：杨新武[1] 刘椿年[1] 

机构地区：[1]北京工业大学计算机学院多媒体与智能软件技术北京市重点实验室,北京100022

出　　处：《计算机工程与应用》2007年第20期25-27,158,共4页Computer Engineering and Applications

基　　金：国家自然科学基金(the National Natural Science Foundation of China under Grant No.60496322);北京市优秀人才基金(No.20051D0501508)

摘　　要：基于适应度比例的选择策略是遗传算法的基本选择方法,但采用该策略易出现未成熟收敛和随机漫游现象。通过实验分析了两种现象的成因,提出采用自适应的比例选择策略来依据种群性状的改变而动态地调整选择压力,进而调整算法求精和求泛能力的平衡。分析和对比实验证实,新的选择策略可有效克服未成熟收敛和随机漫游现象。The fitness-proportionate selection is the basic selection method for genetic algorithm,but it tends toward resulting in the premature convergence and the random walk phenomena.The paper analyzes causes of the two phenomenas by experiment, and argues for adopting a self-adaptive proportional selection strategy to adjust dynamically the selection intensity according to the change of the population state,so adjust dynamically the balance of the refining performance and the reforming performance of genetic algorithm.The analysis and comparative experiment show that the new selection strtegy can overcome the premature convergence and the random walk phenomena.

关 键 词：遗传算法 自适应选择 未成熟收敛 随机漫游 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]