A Maturity-based Adaptive Ant Colony Optimization Algorithm

被引：1

作者：

Wang, Haining ^{[1
]}

Sun, Shouqian ^{[1
]}

Liu, Bo ^{[2
]}

机构：

[1] Zhejiang Univ, Inst Modern Ind Design, Hangzhou 310027, Zhejiang, Peoples R China

[2] Cent S Univ, Inst Informat Sci & Engn, Changsha 410083, Peoples R China

来源：

INTELLIGENT STRUCTURE AND VIBRATION CONTROL, PTS 1 AND 2 | 2011年 / 50-51卷

关键词：

Ant colony optimization; Average path similarity; Adaptive parameter control;

D O I：

10.4028/www.scientific.net/AMM.50-51.353

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

In this paper, for the problems of low convergence rate and getting trapped in local optima easily, the average path similarity (APS) was proposed to present the optimization maturity by analyzing the relationship between parameters of local pheromone updating and global pheromone updating, as well as the optimizing capacity and convergence rate. Furthermore, the coefficients of pheromone updating adaptively were adjusted to improve the convergence rate and prevent the algorithm from getting stuck in local optima. The adaptive ACS has been applied to optimize several benchmark TSP instances. The solution quality and convergence rate of the algorithm were compared comprehensively with conventional ACS to verify the validity and the effectiveness.

引用

页码：353 / +

页数：2

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