一种高效自学习性回溯搜索优化算法

›› 2015, Vol. 28 ›› Issue (2): 41-.

一种高效自学习性回溯搜索优化算法

田文凯

(西安电子科技大学数学与统计学院,陕西西安 710126)

出版日期:2015-02-15 发布日期:2015-02-16
作者简介:田文凯(1990—),男,硕士研究生。研究方向:进化算法,智能优化算法。E-mail:tianwenkai90@126.com

Effective Self-learning Backtracking Search Optimization Algorithm

TIAN Wenkai

(School of Mathematics and Statistics,Xidian University,Xi'an 710126,China)

Online:2015-02-15 Published:2015-02-16

摘要/Abstract

摘要：

针对回溯搜索优化算法收敛速度慢的问题,文中在理论分析的基础上,分别对变异算子和交叉算子进行了改进。设计了双种群引导形式的变异算子,并引入一种基于麦克斯韦-玻尔兹曼分布变异尺度系数,有效地增加了变异方程的搜索效率,并设计了一种带有自学习性的交叉策略,使得回溯搜索优化算法的收敛速度和全局搜索性能均得到了一定的提高,通过数值实验,说明了改进的有效性。

关键词: 回溯搜索优化算法, 麦克斯韦-玻尔兹曼分布, 变异尺度系数, 自学习性, 差分进化算法

Abstract:

For slow convergence speedof Backtracking Search Optimization Algorithm(BSA),this paper makes some improvements on mutation operator and crossover operator on base of theoretical analysis.Firstly,a mutation operator with two-population guided form is designed,anda novel mutation scale factor based on Maxwell-Boltzmann distribution is introduced,which enhance search efficiency of mutation equation effectively.Secondly,crossover strategy is designed with self-learning property,both them enhance the performance of BSA,and numericalexperiments for testing the improved BSA are given in the end.

Key words: backtracking search optimization algorithm;maxwell boltzmann distribution;mutation scale factor;self learning property;differential evolutionary algorithm

中图分类号:

TP301.6

田文凯. 一种高效自学习性回溯搜索优化算法[J]. , 2015, 28(2): 41-.

TIAN Wenkai. Effective Self-learning Backtracking Search Optimization Algorithm[J]. , 2015, 28(2): 41-.

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