基于分布式估计算法的群体智能优化

doi:10.3969/j.issn.1006-2475.2017.01.004

计算机与现代化

基于分布式估计算法的群体智能优化

(1.北京邮电大学理学院，北京 100876; 2.北京邮电大学经济管理学院，北京 100876)

收稿日期:2016-06-22 出版日期:2017-01-12 发布日期:2017-01-11
作者简介:薛焕然(1994-)，男，辽宁沈阳人，北京邮电大学理学院本科生，研究方向：进化计算，数值优化; 江涛(1994-)，男，福建宁德人，本科生，研究方向：统计学，最优化; 郑聪(1995-)，女，北京邮电大学经济管理学院本科生，研究方向：经济学。

Swarm Intelligence Optimization Based on Estimation of Distribution Algorithm

(1. School of Sciences, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. School of Economics and Management, Beijing University of Posts and Telecommunications, Beijing 100876, China)

Received:2016-06-22 Online:2017-01-12 Published:2017-01-11

摘要/Abstract

摘要： 为了更好地求解连续函数最优化问题，对基于正态分布的分布式估计算法进行改进，在原算法的基础上引入优势替换、竞争和模式搜索等机制。为了验证所提策略和算法的有效性，对所提出的5种改进算法进行比较，证明改进的策略模块是有效的，相比现有算法能够收敛到更好的解。对5种算法进行数值仿真，求出每种函数在不同测试函数下30次实验后的平均适应值，以及描述算法稳定性的若干统计量。最后基于数值仿真的结果，对改进效果进行分析讨论。

关键词: 分布估计算法(EDA), 群体智能, 正态分布, 模式搜索

Abstract: In order to solve the numerical optimization problem, the estimation of distribution algorithm based on normal distribution is researched and improved. On the basis of the existing algorithms, the replacement strategy with advantages, competing mechanism and pattern search are introduced. Compared with five kinds of improved algorithms, it is proved that the proposed strategies and the modified algorithms are effective and can find even better solutions. Finally, the effects of improvement are explained based on the numerical simulations and statistical analysis.

Key words: estimation of distribution algorithm (EDA), swarm intelligence, normal distribution, pattern search

中图分类号:

TP18

薛焕然1，江涛1，郑聪2. 基于分布式估计算法的群体智能优化[J]. 计算机与现代化, doi: 10.3969/j.issn.1006-2475.2017.01.004.

XUE Huan-ran1, JIANG Tao1, ZHENG Cong2. Swarm Intelligence Optimization Based on Estimation of Distribution Algorithm[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.01.004.

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基于分布式估计算法的群体智能优化

Swarm Intelligence Optimization Based on Estimation of Distribution Algorithm

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