摘要
本文利用数论中的佳点集理论和方法 ,给出了佳点集遗传算法。将佳点集GA算法应用于求解几类典型的组合优化问题 ,并与传统GA算法进行比较 ,可以看出该算法不仅提高了求解的效率和精度 ,还有效地避免了“早熟”现象。
In this paper, on the basis of the good-point set theory, a good-point set genetic algorithm is designed. The new algorithm is applied to some typical combinatorial optimization problem. Being compared with traditional GA, the satisfied emulation results show that the good-point set GA not only improves efficiency and accuracy, but also effectively avoids the prematurity. [
出处
《微机发展》
2000年第5期1-3,共3页
Microcomputer Development
基金
国家 973基金资助项目!(G1 9980 1 30 50 9)
关键词
传统遗传算法
佳点集遗传算法
组合优化
数论
Traditional GA(GA)
Good-point Set GA(GGA)
Combinatorial Optimization
