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A columnar competitive model for solving multi-traveling salesman problem

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  • Qu, Hong
  • Yi, Zhang
  • Tang, HuaJin

Abstract

This paper studies an optimization problem: multi-traveling salesman problem (MTSP), which is an extension of the well known TSP. A columnar competitive model (CCM) of neural networks incorporates with a winner-take-all learning rule is employed to solve the MTSP. Stability conditions of CCM for MTSP is exploited by mathematical analysis. Parameters settings of the network for guaranteeing the network converges to valid solutions are discussed in detail. Simulations are carried out to illustrate the performance of the columnar competitive model compare to the heuristic algorithms: Tabu Search.

Suggested Citation

  • Qu, Hong & Yi, Zhang & Tang, HuaJin, 2007. "A columnar competitive model for solving multi-traveling salesman problem," Chaos, Solitons & Fractals, Elsevier, vol. 31(4), pages 1009-1019.
    • Handle: RePEc:eee:chsofr:v:31:y:2007:i:4:p:1009-1019
    DOI: 10.1016/j.chaos.2005.10.059
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    Cited by:

    1. Lining Xing & Yuanyuan Liu & Haiyan Li & Chin-Chia Wu & Win-Chin Lin & Xin Chen, 2020. "A Novel Tabu Search Algorithm for Multi-AGV Routing Problem," Mathematics, MDPI, vol. 8(2), pages 1-16, February.

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