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A branch-and-cut algorithm for the plant-cycle location problem

Author

Listed:
  • M Labbé

    (ISRO and SMG, Université Libre de Bruxelles)

  • I Rodríguez-Martin

    (DEIOC, Universidad de La Laguna, La Laguna)

  • J J Salazar-González

    (DEIOC, Universidad de La Laguna, La Laguna)

Abstract

The Plant-Cycle Location Problem (PCLP) is defined on a graph G=(I∪J, E), where I is the set of customers and J is the set of plants. Each customer must be served by one plant, and the plant must be opened to serve customers. The number of customers that a plant can serve is limited. There is a cost of opening a plant, and of serving a customer from an open plant. All customers served by a plant are in a cycle containing the plant, and there is a routing cost associated to each edge of the cycle. The PCLP consists in determining which plants to open, the assignment of customers to plants, and the cycles containing each open plant and its customers, minimizing the total cost. It is an NP-hard optimization problem arising in routing and telecommunications. In this article, the PCLP is formulated as an integer linear program, a branch-and-cut algorithm is developed, and computational results on real-world data and randomly generated instances are presented. The proposed approach is able to find optimal solutions of random instances with up to 100 customers and 100 potential plants, and of instances on real-world data with up to 120 customers and 16 potential plants.

Suggested Citation

  • M Labbé & I Rodríguez-Martin & J J Salazar-González, 2004. "A branch-and-cut algorithm for the plant-cycle location problem," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(5), pages 513-520, May.
  • Handle: RePEc:pal:jorsoc:v:55:y:2004:i:5:d:10.1057_palgrave.jors.2601692
    DOI: 10.1057/palgrave.jors.2601692
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    References listed on IDEAS

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    Cited by:

    1. Mohammad M. Fazel-Zarandi & J. Christopher Beck, 2012. "Using Logic-Based Benders Decomposition to Solve the Capacity- and Distance-Constrained Plant Location Problem," INFORMS Journal on Computing, INFORMS, vol. 24(3), pages 387-398, August.
    2. Bagheri Hosseini, Mozhde & Dehghanian, Farzad & Salari, Majid, 2019. "Selective capacitated location-routing problem with incentive-dependent returns in designing used products collection network," European Journal of Operational Research, Elsevier, vol. 272(2), pages 655-673.
    3. Neamatian Monemi, Rahimeh & Gelareh, Shahin & Nagih, Anass & Maculan, Nelson & Danach, Kassem, 2021. "Multi-period hub location problem with serial demands: A case study of humanitarian aids distribution in Lebanon," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    4. Patrick Schittekat & Kenneth Sörensen, 2009. "OR Practice---Supporting 3PL Decisions in the Automotive Industry by Generating Diverse Solutions to a Large-Scale Location-Routing Problem," Operations Research, INFORMS, vol. 57(5), pages 1058-1067, October.
    5. Venkatesh Pandiri & Alok Singh, 2021. "A simple hyper-heuristic approach for a variant of many-to-many hub location-routing problem," Journal of Heuristics, Springer, vol. 27(5), pages 791-868, October.

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