A Modified Ant Colony Algorithm for Traveling Salesman Problem

被引：10
|
作者：
Wei, X. [1 ]
Han, L. [1 ]
Hong, L. [1 ]
机构：
[1] Weifang Univ, Sch Comp Engn, Weifang 261061, Peoples R China
来源：
INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL | 2014年 / 9卷 / 05期
关键词：
Traveling Salesman Problem (TSP); Ant Colony Optimization (ACO); Cultural Algorithm (CA); VEHICLE-ROUTING PROBLEM; ACO ALGORITHM; OPTIMIZATION ALGORITHMS; SYSTEM; CONVERGENCE;
D O I：
10.15837/ijccc.2014.5.1280
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Ant colony algorithms such as Ant Colony Optimization (ACO) have been effectively applied to solve the Traveling Salesman problem (TSP). However, traditional ACO algorithm has some issues such as long iterative length and prone to local convergence. To this end, we propose we embed AGO into Cultural Algorithm (CA) framework by leveraging the dual inheritance mechanism. Best solutions are evolved in both population space and belief space, and the communication between them is achieved by accept and influence operations. Besides, we employ multiple population spaces for parallel execution. Experiments show that the performance of our proposed algorithm is greatly improved.
引用
收藏
页码：633 / 643
页数：11
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