首页 | 本学科首页   官方微博 | 高级检索  
     

遗传算法的改进
引用本文:韩万林,张幼蒂. 遗传算法的改进[J]. 中国矿业大学学报, 2000, 29(1): 102-105
作者姓名:韩万林  张幼蒂
作者单位:中国矿业大学,采矿工程系,江苏,徐州,221008
基金项目:高等学校博士学科点专项科研基金!96029002
摘    要:遗传算法是建立在遗传学与自然选择基础上的自适应索过程,作为解决复杂问题的一种有效手段,遗传算法是目前人工智能和系统优化领域的热点研究课题。但是,在实际应用中,简单跗算法存在收剑速度慢和稳定性差等缺陷。为克服这些问题,在对遗传算法的基本要点进行介绍的基础上,对交换、突变和复制等算子以及操作过程进行了改进。为了验证改进遗传算法的可行性与有效性,进行了多峰值函数的优化。试验结果表明,改进遗传3算法提高了

关 键 词:遗传算法 多峰值函数 优化 改进 人工智能
文章编号:1000-1964(2000)01-0102-04
修稿时间:1999

Improvement of Genetic Algorithm
Han Wan-lin,Zhang You-di. Improvement of Genetic Algorithm[J]. Journal of China University of Mining & Technology, 2000, 29(1): 102-105
Authors:Han Wan-lin  Zhang You-di
Abstract:Genetic algorithm, based on the mechanism ofgenetics and natural selection, is an adaptive searching procedure. As a powerful approachapplied to complex problems, genetic algorithm is a hot point for research on the fieldsof artificial intelligence and system optimization. However, simple genetic algorithm hasdrawbacks such as slow convergence and less stability in actual uses. To overcome theseproblems, crossover, mutation and reproduction operators as well as the procedure areimproved based on introduction of the principles. Multimodal function optimization isperformed to verify the feasibility and effectiveness. The experiment results show thatconvergence speed and stability are increased by improved genetic algorithm.
Keywords:genetic algorithm  multimodal function optimization  improvement
本文献已被 CNKI 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号