Parallelized genetic ant colony systems for solving the traveling salesman problem

被引：80

作者：

Chen, Shyi-Ming ^{[1
]}

Chien, Chih-Yao ^{[1
]}

机构：

[1] Natl Taiwan Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taipei, Taiwan

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2011年 / 38卷 / 04期

关键词：

Traveling salesman problem; Ant colony systems; Genetic algorithms; Parallelization; Parallelized genetic ant colony systems; OPTIMIZATION; ALGORITHM;

D O I：

10.1016/j.eswa.2010.09.048

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we present a new method, called the parallelized genetic ant colony system (PGACS), for solving the traveling salesman problem. It consists of the genetic algorithm, including the new crossover operations and the hybrid mutation operations, and the ant colony systems with communication strategies. We also make an experiment with three classical data sets got from the TSP library to test the performance of the proposed method. The experiment results show that the performance of the proposed method is better than Chu et al.'s method (2004). (c) 2010 Elsevier Ltd. All rights reserved.

引用

页码：3873 / 3883

页数：11

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