改进的人工蜂群算法在函数优化问题中的应用

计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (19): 36-39.

改进的人工蜂群算法在函数优化问题中的应用

王慧颖，刘建军，王全洲

中国石油大学（北京）数理学院，北京 102249

出版日期:2012-07-01 发布日期:2012-06-27

Modified artificial bee colony algorithm for numerical function optimization

WANG Huiying, LIU Jianjun, WANG Quanzhou

College of Mathematics and Physics, China University of Petroleum（Beijing）, Beijing 102249, China

Online:2012-07-01 Published:2012-06-27

摘要/Abstract

摘要： 人工蜂群算法是近年来新提出的一种优化算法。针对标准人工蜂群算法的局部搜索能力差，精度低的缺点，提出了一个改进的人工蜂群算法，利用全局最优解和个体极值的信息来改进人工蜂群算法中的搜索模式，并引入异步变化学习因子，保持全局搜索和局部搜索的平衡。将改进的人工蜂群算法在函数优化问题上进行测试，结果表明改进的人工蜂群算法优于原算法。

关键词: 人工蜂群算法（ABC）, 异步变化学习因子, 函数优化问题

Abstract: In recent years, a new optimization algorithm called artificially colony algorithm has proposed. The standard artificial bee algorithm is weak at the locally searching capability and precision, a modified Artificial Bee Colony（ABC） algorithm is proposed whose core is to integrate the information of global best solution and previous best solution into the solution search equation of ABC, achieves the information exchange of groups. Meanwhile asynchronization variable learning factor introduced here is to keep the balance between the global search and the local search. The tests for continuous function optimization show that the new algorithm is superior to conventional ABC algorithm in quality.

Key words: Artificial Bee Colony（ABC）, asynchronization variable learning factor, numerical function optimization

王慧颖，刘建军，王全洲. 改进的人工蜂群算法在函数优化问题中的应用[J]. 计算机工程与应用, 2012, 48(19): 36-39.

WANG Huiying, LIU Jianjun, WANG Quanzhou. Modified artificial bee colony algorithm for numerical function optimization[J]. Computer Engineering and Applications, 2012, 48(19): 36-39.

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