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A DC programming heuristic applied to the logistics network design problem

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  • Thanh, Phuong Nga
  • Bostel, Nathalie
  • Péton, Olivier

Abstract

This paper proposes a new heuristic method for the logistics network design and planning problem based on linear relaxation and DC (difference of convex functions) programming. We consider a multi-period, multi-echelon, multi-commodity and multi-product problem defined as a large scale mixed integer linear programming (MILP) model. The method is experimented on data sets of various size. The numerical results validate the efficiency of the heuristic for instances with up to several dozens facilities, 18 products and 270 retailers.

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  • Thanh, Phuong Nga & Bostel, Nathalie & Péton, Olivier, 2012. "A DC programming heuristic applied to the logistics network design problem," International Journal of Production Economics, Elsevier, vol. 135(1), pages 94-105.
    • Handle: RePEc:eee:proeco:v:135:y:2012:i:1:p:94-105
    DOI: 10.1016/j.ijpe.2010.09.025
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    References listed on IDEAS

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    Cited by:

    1. Hong, Jiangtao & Diabat, Ali & Panicker, Vinay V. & Rajagopalan, Sridharan, 2018. "A two-stage supply chain problem with fixed costs: An ant colony optimization approach," International Journal of Production Economics, Elsevier, vol. 204(C), pages 214-226.
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    3. Cortinhal, M. J. & Lopes, M. J. & Melo, M. T., 2014. "Redesigning a three-echelon logistics network over multiple time periods with transportation mode selection and outsourcing opportunities," Technical Reports on Logistics of the Saarland Business School 7, Saarland University of Applied Sciences (htw saar), Saarland Business School.

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