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Local Search for the Asymmetric Traveling Salesman Problem

Author

Listed:
  • Paris-C. Kanellakis

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

  • Christos H. Papadimitriou

    (Massachusetts Institute of Technology, Cambridge, Massachusetts)

Abstract

We present an extension of the Lin-Kernighan local search algorithm for the solution of the asymmetric traveling salesman problem. Computational results suggest that our heuristic is feasible for fairly large instances. We also present some theoretical results which guided our design of the heuristic.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:oropre:v:28:y:1980:i:5:p:1086-1099
    DOI: 10.1287/opre.28.5.1086
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    Citations

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    Cited by:

    1. C Gagné & M Gravel & W L Price, 2005. "Using metaheuristic compromise programming for the solution of multiple-objective scheduling problems," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(6), pages 687-698, June.
    2. K Sang-Ho & G Young-Gun & K Maing-Kyu, 2003. "Application of the out-of-kilter algorithm to the asymmetric traveling salesman problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(10), pages 1085-1092, October.
    3. Rego, César & Gamboa, Dorabela & Glover, Fred & Osterman, Colin, 2011. "Traveling salesman problem heuristics: Leading methods, implementations and latest advances," European Journal of Operational Research, Elsevier, vol. 211(3), pages 427-441, June.
    4. Pan-Li Zhang & Xiao-Bo Sun & Ji-Quan Wang & Hao-Hao Song & Jin-Ling Bei & Hong-Yu Zhang, 2022. "The Discrete Carnivorous Plant Algorithm with Similarity Elimination Applied to the Traveling Salesman Problem," Mathematics, MDPI, vol. 10(18), pages 1-34, September.
    5. 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.
    6. Gary R. Waissi & Pragya Kaushal, 2020. "A polynomial matrix processing heuristic algorithm for finding high quality feasible solutions for the TSP," OPSEARCH, Springer;Operational Research Society of India, vol. 57(1), pages 73-87, March.
    7. César Rego & Fred Glover, 2010. "Ejection chain and filter-and-fan methods in combinatorial optimization," Annals of Operations Research, Springer, vol. 175(1), pages 77-105, March.
    8. Nikolakopoulos, Athanassios & Sarimveis, Haralambos, 2007. "A threshold accepting heuristic with intense local search for the solution of special instances of the traveling salesman problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1911-1929, March.
    9. Egon Balas & Neil Simonetti, 2001. "Linear Time Dynamic-Programming Algorithms for New Classes of Restricted TSPs: A Computational Study," INFORMS Journal on Computing, INFORMS, vol. 13(1), pages 56-75, February.

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