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A Multi-MetaHeuristic Combined ACS-TSP System

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7003))

Abstract

This paper presents a Multi-MetaHeuristic combined Ant Colony System (ACS)-Travelling Salesman Problem(TSP) algorithm for solving the TSP. We introduce genetic algorithm in ACS-TSP to search solutions space for dealing with the early stagnation problem of the traveling salesman problem. Moreover, we present a new strategy of Minimum Spanning Tree (MST) coupled with Nearest Neighbor(NN) to construct a initial tour for improving TSP thus obtaining good solutions quickly. According to our simulation results, the new algorithm can provide a significantly improvement for obtaining a global optimum solution or a near global optimum solution in large TSPs.

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© 2011 Springer-Verlag Berlin Heidelberg

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Meng, L., Wang, L. (2011). A Multi-MetaHeuristic Combined ACS-TSP System. In: Deng, H., Miao, D., Lei, J., Wang, F.L. (eds) Artificial Intelligence and Computational Intelligence. AICI 2011. Lecture Notes in Computer Science(), vol 7003. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23887-1_3

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  • DOI: https://doi.org/10.1007/978-3-642-23887-1_3

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-23886-4

  • Online ISBN: 978-3-642-23887-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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