Advanced harmony search with ant colony optimization for solving the traveling salesman problem

Ho Yoeng Yun, Suk Jae Jeong, Kyung Sup Kim

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

We propose a novel heuristic algorithm based on the methods of advanced Harmony Search and Ant Colony Optimization (AHS-ACO) to effectively solve the Traveling Salesman Problem (TSP). The TSP, in general, is well known as an NP-complete problem, whose computational complexity increases exponentially by increasing the number of cities. In our algorithm, Ant Colony Optimization (ACO) is used to search the local optimum in the solution space, followed by the use of the Harmony Search to escape the local optimum determined by the ACO and to move towards a global optimum. Experiments were performed to validate the efficiency of our algorithm through a comparison with other algorithms and the optimum solutions presented in the TSPLIB. The results indicate that our algorithm is capable of generating the optimum solution for most instances in the TSPLIB; moreover, our algorithm found better solutions in two cases (kroB100 and pr144) when compared with the optimum solution presented in the TSPLIB.

Original languageEnglish
Article number123738
JournalJournal of Applied Mathematics
Volume2013
DOIs
Publication statusPublished - 2013 Dec 1

Fingerprint

Harmony Search
Traveling salesman problem
Ant colony optimization
Travelling salesman problems
Computational complexity
Global Optimum
Heuristic algorithms
Heuristic algorithm
Computational Complexity
NP-complete problem
Experiment
Experiments

All Science Journal Classification (ASJC) codes

  • Applied Mathematics

Cite this

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Advanced harmony search with ant colony optimization for solving the traveling salesman problem. / Yun, Ho Yoeng; Jeong, Suk Jae; Kim, Kyung Sup.

In: Journal of Applied Mathematics, Vol. 2013, 123738, 01.12.2013.

Research output: Contribution to journalArticle

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