A Modified Ant Colony Algorithm for Traveling Salesman Problem

  • Xianmin Wei School of computer engineering, Weifang University, Weifang 261061, P.R. China
  • Liqi Han School of computer engineering, Weifang University, Weifang 261061, P.R. China
  • Lu Hong School of computer engineering, Weifang University, Weifang 261061, P.R. China

Abstract

Ant colony algorithms such as Ant Colony Optimization (ACO) havebeen effectively applied to solve the Traveling Salesman problem (TSP). However,traditional ACO algorithm has some issues such as long iterative length and prone tolocal convergence. To this end, we propose we embed ACO into Cultural Algorithm(CA) framework by leveraging the dual inheritance mechanism. Best solutions areevolved in both population space and belief space, and the communication betweenthem is achieved by accept and influence operations. Besides, we employ multiplepopulation spaces for parallel execution. Experiments show that the performance ofour proposed algorithm is greatly improved.

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Published
2014-08-05
How to Cite
WEI, Xianmin; HAN, Liqi; HONG, Lu. A Modified Ant Colony Algorithm for Traveling Salesman Problem. INTERNATIONAL JOURNAL OF COMPUTERS COMMUNICATIONS & CONTROL, [S.l.], v. 9, n. 5, p. 633-643, aug. 2014. ISSN 1841-9844. Available at: <http://univagora.ro/jour/index.php/ijccc/article/view/1280>. Date accessed: 02 july 2020. doi: https://doi.org/10.15837/ijccc.2014.5.1280.

Keywords

Traveling Salesman Problem (TSP), Ant Colony Optimization (ACO), Cultural Algorithm (CA)