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An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups

Author

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  • Ana María Anaya-Arenas
  • Caroline Prodhon
  • Jacques Renaud
  • Angel Ruiz

Abstract

This article addresses a new version of the biomedical sample transportation problem, as a vehicle routing problem with precedence constraints arising in the context of healthcare logistics, and proposes an iterated local search algorithm to solve it. This new version is more realistic and complex since it considers the collection centres’ opening hours and the moment at which they are visited as decision variables, granting additional flexibility to elaborate more efficient routes. Indeed, this problem is harder to model and to solve than its previous version because the constraint on the short samples’ lifetime leads to interdependency between successive pickups at each collection center. A metaheuristic is thus proposed to solve real-life instances. Numerical experiments confirm (1) the value of simultaneously planning routes, opening hours, and visit hours (which is new in the literature) and (2) the efficiency of the proposed algorithm to solve this problem.

Suggested Citation

  • Ana María Anaya-Arenas & Caroline Prodhon & Jacques Renaud & Angel Ruiz, 2021. "An iterated local search for the biomedical sample transportation problem with multiple and interdependent pickups," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(2), pages 367-382, February.
    • Handle: RePEc:taf:tjorxx:v:72:y:2021:i:2:p:367-382
    DOI: 10.1080/01605682.2019.1657369
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