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Hierarchical Solving Method for Large Scale TSP Problems

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Advances in Neural Networks – ISNN 2014 (ISNN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8866))

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Abstract

This paper presents a hierarchical algorithm for solving large-scale traveling salesman problem (TSP), the algorithm first uses clustering algorithms to large-scale TSP problem into a number of small-scale collections of cities, and then put this TSP problem as a generalized traveling salesman problem (GTSP), convert solving large-scale TSP problem into solving GTSP and several small-scale TSP problems. Then all the sub-problems will be solved by ant colony algorithm and At last all the solutions of each sub-problem will be merged into the solution of the large-scale TSP problem by solution of GTSP. Experimental part we uses the traditional ant colony algorithm and new algorithm for solving large-scale TSP problem, numerical simulation results show that the proposed algorithm for large-scale TSP problem has a good effect, compared with the traditional ant colony algorithm, the solving efficiency has been significantly improved.

Supported by the National Natural Science Foundation of China under Grant No. 61163034, 61373067 and Inner Mongolia Natural Science Foundation under Grant No. 2013MS0910, 2013MS0911.

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Authors and Affiliations

  1. College of Computer Science and Technology, Inner Mongolia University for Nationalities, Tongliao, China

    Jingqing Jiang & Zhili Pei

  2. College of Mathematics, Inner Mongolia University for Nationalities, Tongliao, China

    Jingqing Jiang, Jingying Gao & Zhili Pei

  3. College of Computer Science and Technology, Jilin University, Changchun, China

    Gaoyang Li & Chunguo Wu

Authors
  1. Jingqing Jiang
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  2. Jingying Gao
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  3. Gaoyang Li
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  4. Chunguo Wu
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  5. Zhili Pei
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Corresponding author

Correspondence to Jingqing Jiang .

Editor information

Editors and Affiliations

  1. Wuhan, China

    Zhigang Zeng

  2. University of Macau, Macau, Macao

    Yangmin Li

  3. The Chinese University of Hong Kong, Hong Kong, Hong Kong, Hong Kong SAR

    Irwin King

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© 2014 Springer International Publishing Switzerland

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Jiang, J., Gao, J., Li, G., Wu, C., Pei, Z. (2014). Hierarchical Solving Method for Large Scale TSP Problems. In: Zeng, Z., Li, Y., King, I. (eds) Advances in Neural Networks – ISNN 2014. ISNN 2014. Lecture Notes in Computer Science(), vol 8866. Springer, Cham. https://doi.org/10.1007/978-3-319-12436-0_28

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  • DOI: https://doi.org/10.1007/978-3-319-12436-0_28

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12435-3

  • Online ISBN: 978-3-319-12436-0

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