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Discrete parallel machine makespan ScheLoc problem

Author

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  • Corinna Heßler

    (TU Kaiserslautern)

  • Kaouthar Deghdak

    (Normandie Univ
    Université François-Rabelais)

Abstract

Scheduling–Location (ScheLoc) problems integrate the separate fields of scheduling and location problems. In ScheLoc problems the objective is to find locations for the machines and a schedule for each machine subject to some production and location constraints such that some scheduling objective is minimized. In this paper we consider the discrete parallel machine makespan ScheLoc problem where the set of possible machine locations is discrete and a set of n jobs has to be taken to the machines and processed such that the makespan is minimized. Since the separate location and scheduling problem are both $$\mathcal {NP}$$ NP -hard, so is the corresponding ScheLoc problem. Therefore, we propose an integer programming formulation and different versions of clustering heuristics, where jobs are split into clusters and each cluster is assigned to one of the possible machine locations. Since the IP formulation can only be solved for small scale instances we propose several lower bounds to measure the quality of the clustering heuristics. Extensive computational tests show the efficiency of the heuristics.

Suggested Citation

  • Corinna Heßler & Kaouthar Deghdak, 2017. "Discrete parallel machine makespan ScheLoc problem," Journal of Combinatorial Optimization, Springer, vol. 34(4), pages 1159-1186, November.
    • Handle: RePEc:spr:jcomop:v:34:y:2017:i:4:d:10.1007_s10878-017-0138-9
    DOI: 10.1007/s10878-017-0138-9
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    References listed on IDEAS

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    1. Mladenovic, Nenad & Brimberg, Jack & Hansen, Pierre & Moreno-Perez, Jose A., 2007. "The p-median problem: A survey of metaheuristic approaches," European Journal of Operational Research, Elsevier, vol. 179(3), pages 927-939, June.
    2. Barbaros C. Tansel & Richard L. Francis & Timothy J. Lowe, 1983. "State of the Art---Location on Networks: A Survey. Part I: The p-Center and p-Median Problems," Management Science, INFORMS, vol. 29(4), pages 482-497, April.
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    Cited by:

    1. Yantong Li & Jean-François Côté & Leandro Callegari-Coelho & Peng Wu, 2022. "Novel Formulations and Logic-Based Benders Decomposition for the Integrated Parallel Machine Scheduling and Location Problem," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 1048-1069, March.

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