摘要
遗传算法作为一种通用随机搜索算法,在函数优化、机器学习等许多方面获得了很好的结果.但是,常规的遗传操作对于有序问题效果不理想.本文分析了一种典型的有序问题——旅行售货员问题,根据其特点并结合遗传算法的模式理论,设计出一个新的启发式遗传交换操作.理论分析和实验结果显示这种交换操作的效果大大好于较通用的有序交换操作,也优于Grefenstette的贪心方法.
As general stochastic search algorithms, geneitc algorithms (GA's) have been applied to a variety of research fields such as function optimization, machine learning, etc.. Classical GA's can not surmount the ordering problems well. In this paper, for a kind of classical ordering problems——the traveling salesman problem, we first illustrate the necessity of using normalization techniques to calculate appropriate evaluation functions and then design a new heuristic crossover operator which is more effective than similar operators published before.
出处
《计算机研究与发展》
EI
CSCD
北大核心
1992年第9期14-19,共6页
Journal of Computer Research and Development
基金
国家863高技术计划
关键词
遗传算法
TSP问题
交换操作
genetic algorithm
traveling salesman problem
crossover operation
