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A rough-cut approach for evaluating location-routing decisions via approximation algorithms

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  • Menezes, Mozart B.C.
  • Ruiz-Hernández, Diego
  • Verter, Vedat

Abstract

The first step in most location-routing projects involves bringing the primary stakeholders on board and securing funding for implementation of the required changes. To this end, practitioners often need a good feasible solution together with a lower bound on the cost of any solution to the problem at hand, rather than exact solutions based on detailed and accurate parameter estimates. In this article, we present a simple methodology for assessing the quality of the current distribution network as well as for identifying opportunities for improvement. We incorporate the potential use of different transportation technologies at different layers of the network. We demonstrate the versatility of the proposed rough-cut approach by means of two real life implementations: (i) redesigning the supply network of the Casino Group, a supermarket chain in southeast France, and (ii) redesigning the household material recycling network of the city of Calgary, in Canada.

Suggested Citation

  • Menezes, Mozart B.C. & Ruiz-Hernández, Diego & Verter, Vedat, 2016. "A rough-cut approach for evaluating location-routing decisions via approximation algorithms," Transportation Research Part B: Methodological, Elsevier, vol. 87(C), pages 89-106.
    • Handle: RePEc:eee:transb:v:87:y:2016:i:c:p:89-106
    DOI: 10.1016/j.trb.2016.03.003
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    2. Peng Xing & Xiangru Zhao & Mingxing Wang, 2022. "The Optimal Combination between Recycling Channel and Logistics Service Outsourcing in a Closed-Loop Supply Chain Considering Consumers’ Environmental Awareness," Sustainability, MDPI, vol. 14(24), pages 1-25, December.
    3. Zhu, Stuart X. & Ursavas, Evrim, 2018. "Design and analysis of a satellite network with direct delivery in the pharmaceutical industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 116(C), pages 190-207.
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    5. Schuster Puga, Matías & Tancrez, Jean-Sébastien, 2017. "A heuristic algorithm for solving large location–inventory problems with demand uncertainty," European Journal of Operational Research, Elsevier, vol. 259(2), pages 413-423.

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