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A distribution-free TSP tour length estimation model for random graphs

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  • Çavdar, Bahar
  • Sokol, Joel

Abstract

Traveling Salesman Problem (TSP) tour length estimations can be used when it is not necessary to know an exact tour, e.g., when using certain heuristics to solve location-routing problems. The best estimation models in the TSP literature focus on random instances where the node dispersion is known; those that do not require knowledge of node dispersion are either less accurate or slower. In this paper, we develop a new regression-based tour length estimation model that is distribution-free, accurate, and fast, with a small standard deviation of the estimation errors. When the distribution of the node coordinates is known, it provides a close estimate of the well-known asymptotic tour length estimation formula of Beardwood et al. (1959); more importantly, when the distribution is unknown or non-integrable so Beardwood et al.’s estimation cannot be used, our model still provides good, fast tour length estimates.

Suggested Citation

  • Çavdar, Bahar & Sokol, Joel, 2015. "A distribution-free TSP tour length estimation model for random graphs," European Journal of Operational Research, Elsevier, vol. 243(2), pages 588-598.
    • Handle: RePEc:eee:ejores:v:243:y:2015:i:2:p:588-598
    DOI: 10.1016/j.ejor.2014.12.020
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    Cited by:

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    7. Ansari, Sina & Başdere, Mehmet & Li, Xiaopeng & Ouyang, Yanfeng & Smilowitz, Karen, 2018. "Advancements in continuous approximation models for logistics and transportation systems: 1996–2016," Transportation Research Part B: Methodological, Elsevier, vol. 107(C), pages 229-252.
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    Keywords

    TSP; Tour length estimation;

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