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Improved extremal optimization for the asymmetric traveling salesman problem

Author

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  • Chen, Yu-Wang
  • Zhu, Yao-Jia
  • Yang, Gen-Ke
  • Lu, Yong-Zai

Abstract

This paper presents an improved extremal optimization (IEO) algorithm for solving the asymmetric traveling salesman problem (ATSP). At each update step, the IEO algorithm proceeds through two main steps: extremal dynamics and cooperative optimization. As an improvement of extremal optimization (EO), the IEO provides a general combinatorial optimization framework by emphasizing the step of cooperative optimization. In the paper, an effective cooperative optimization strategy with combination of greedy search and random walk is designed in terms of the microscopic characteristics of the ATSP solutions. Simulation results on a set of benchmark ATSP instances show that the proposed IEO algorithm provides satisfactory performance on computational effectiveness and efficiency.

Suggested Citation

  • Chen, Yu-Wang & Zhu, Yao-Jia & Yang, Gen-Ke & Lu, Yong-Zai, 2011. "Improved extremal optimization for the asymmetric traveling salesman problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(23), pages 4459-4465.
  • Handle: RePEc:eee:phsmap:v:390:y:2011:i:23:p:4459-4465
    DOI: 10.1016/j.physa.2011.06.070
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    References listed on IDEAS

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    6. Chen, Yu-Wang & Lu, Yong-Zai & Chen, Peng, 2007. "Optimization with extremal dynamics for the traveling salesman problem," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 385(1), pages 115-123.
    7. Paris-C. Kanellakis & Christos H. Papadimitriou, 1980. "Local Search for the Asymmetric Traveling Salesman Problem," Operations Research, INFORMS, vol. 28(5), pages 1086-1099, October.
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    2. Huang, Zhendong & Xiao, Renbin, 2013. "An emergent computation approach to the problem of polygon layout with performance constraints," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(20), pages 5074-5088.

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