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Models to estimate average route lengths in different geographical environments

Author

Listed:
  • A Hindle

    (Lancaster University)

  • D Worthington

    (Lancaster University)

Abstract

This paper investigates how average route lengths for travelling salesman-type (TSP) journeys are influenced by the pattern and number of points visited. Two mathematical functions to estimate average route lengths are presented. The first function relates to average route lengths when n points are randomly located and the second to average route lengths when certain areas are more likely to be visited than the others, as defined by ‘demand surfaces’. Estimation of route lengths in this way can be a useful tool in the analysis of strategic and operational distribution problems, particularly in public services such as health and social services.

Suggested Citation

  • A Hindle & D Worthington, 2004. "Models to estimate average route lengths in different geographical environments," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(6), pages 662-666, June.
    • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:6:d:10.1057_palgrave.jors.2601751
    DOI: 10.1057/palgrave.jors.2601751
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    Citations

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    Cited by:

    1. Anna Franceschetti & Ola Jabali & Gilbert Laporte, 2017. "Continuous approximation models in freight distribution management," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 25(3), pages 413-433, October.
    2. G A Hindle & A Hindle, 2010. "Developing geographical indicators of mileage-related costs: a case study exploring travelling public services in English local areas," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(5), pages 714-722, May.
    3. 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.
    4. Baller, Annelieke C. & Dabia, Said & Dullaert, Wout E.H. & Vigo, Daniele, 2019. "The Dynamic-Demand Joint Replenishment Problem with Approximated Transportation Costs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 1013-1033.

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    Keywords

    route length; meta-modelling;

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