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Chaotic ant swarm for the traveling salesman problem

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Abstract

Chaotic ant swarm (CAS) is an optimization algorithm based on swarm intelligence theory, which has been applied to find the global optimum solution in continuous search space. However, it is not able to solve the combinational optimization problem directly, e.g., the traveling salesman problem (TSP). To tackle this problem, we propose a new method to solve the traveling salesman problem based on chaotic ant swarm, CAS-TSP for short. The CAS-TSP is developed by introducing a mapping from continuous space to discrete space, reverse operator and crossover operator into the CAS. Computer simulations demonstrate that the CAS-TSP is capable of generating optimal solution to instances of the TSPLIB in almost all test problems of sizes up to 150. Also a comparative computational study shows that this CAS-TSP algorithm is an efficient tool for solving TSP and this heuristic is competitive also with other heuristics.

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Authors and Affiliations

  1. School of Computer and Information, Hefei University of Technology, Hefei, 230009, P.R. China

    Zhen Wei, Fangzhen Ge & Yang Lu

  2. School of Computer Science and Technology, Huaibei Normal University, Huaibei, 235000, P.R. China

    Fangzhen Ge

  3. Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing, 100876, P.R. China

    Lixiang Li & Yixian Yang

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  1. Zhen Wei
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  2. Fangzhen Ge
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  3. Yang Lu
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  4. Lixiang Li
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Correspondence to Fangzhen Ge.

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Wei, Z., Ge, F., Lu, Y. et al. Chaotic ant swarm for the traveling salesman problem. Nonlinear Dyn 65, 271–281 (2011). https://doi.org/10.1007/s11071-010-9889-x

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