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一种嵌入思维进化的新的进化算法

A New Evolutionary Algorithm for Global Optimization Embedded in the Mind Evolutionary Computation
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摘要 对于运筹学问题学中的函数优化问题,本文提出一种嵌入思维进化的新的进化算法,将思维进化计算(Mind Evolutionary Computation,MEC)的"趋同"和"异化"操作加入到进化算法中,充分利用其特有记忆机制、定向机制和探测与开采功能之间的协调机制的好性能,并加入K-meams聚类算法,保证群体多样性。最后,数值模拟验证了新算法的有效性。 A new evolutionary algorithm for global optimization embedded in the mind evolutionary computation for optimal problem in operational reserch is offered in this paper. Operations of similartaxis and dissimilation of mind evolutionary computation join in with the EC to make the best of the good quality of the evolutionary directionality mechanism, memory mechanism and harmony mechanism between exploitation and exploration. Also, K-meams clustering algorithm is used to ensure the diversity of the population. At last, the numerical results also show that the new approach is efficient.
作者 杜金玲 刘大莲 李奇会
机构地区 山东建筑大学管理学院.山东济南 北京联合大学基础教学部
出处 《运筹与管理》 CSSCI CSCD 北大核心 2012年第3期95-98,共4页 Operations Research and Management Science
关键词 运筹学 进化计算 思维进化计算 趋同 异化 聚类 operational resereh evolutionary computation mind evolutionary computatio：a similartaxis dissim-ilation clustering
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献20

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运筹与管理
2012年 第3期

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