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A criterion space decomposition approach to generalized tri-objective tactical resource allocation

Author

Listed:
  • Sunney Fotedar

    (Chalmers University of Technology and University of Gothenburg)

  • Ann-Brith Strömberg

    (Chalmers University of Technology and University of Gothenburg)

  • Torgny Almgren

    (GKN Aerospace Sweden AB)

  • Stefan Cedergren

    (GKN Aerospace Sweden AB)

Abstract

We present a tri-objective mixed-integer linear programming model of the tactical resource allocation problem with inventories, called the generalized tactical resource allocation problem (GTRAP). We propose a specialized criterion space decomposition strategy, in which the projected two-dimensional criterion space is partitioned and the corresponding sub-problems are solved in parallel by application of the quadrant shrinking method (QSM) (Boland in Eur J Oper Res 260(3):873–885, 2017) for identifying non-dominated points. To obtain an efficient implementation of the parallel variant of the QSM we suggest some modifications to reduce redundancies. Our approach is tailored for the GTRAP and is shown to have superior computational performance as compared to using the QSM without parallelization when applied to industrial instances.

Suggested Citation

  • Sunney Fotedar & Ann-Brith Strömberg & Torgny Almgren & Stefan Cedergren, 2023. "A criterion space decomposition approach to generalized tri-objective tactical resource allocation," Computational Management Science, Springer, vol. 20(1), pages 1-28, December.
    • Handle: RePEc:spr:comgts:v:20:y:2023:i:1:d:10.1007_s10287-023-00442-6
    DOI: 10.1007/s10287-023-00442-6
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    References listed on IDEAS

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    1. Dächert, Kerstin & Klamroth, Kathrin & Lacour, Renaud & Vanderpooten, Daniel, 2017. "Efficient computation of the search region in multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 260(3), pages 841-855.
    2. James R. Bradley & Peter W. Glynn, 2002. "Managing Capacity and Inventory Jointly in Manufacturing Systems," Management Science, INFORMS, vol. 48(2), pages 273-288, February.
    3. Laumanns, Marco & Thiele, Lothar & Zitzler, Eckart, 2006. "An efficient, adaptive parameter variation scheme for metaheuristics based on the epsilon-constraint method," European Journal of Operational Research, Elsevier, vol. 169(3), pages 932-942, March.
    4. Boland, Natashia & Charkhgard, Hadi & Savelsbergh, Martin, 2017. "The Quadrant Shrinking Method: A simple and efficient algorithm for solving tri-objective integer programs," European Journal of Operational Research, Elsevier, vol. 260(3), pages 873-885.
    5. Lemesre, J. & Dhaenens, C. & Talbi, E.G., 2007. "An exact parallel method for a bi-objective permutation flowshop problem," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1641-1655, March.
    6. Klamroth, Kathrin & Lacour, Renaud & Vanderpooten, Daniel, 2015. "On the representation of the search region in multi-objective optimization," European Journal of Operational Research, Elsevier, vol. 245(3), pages 767-778.
    7. Nourelfath, Mustapha, 2011. "Service level robustness in stochastic production planning under random machine breakdowns," European Journal of Operational Research, Elsevier, vol. 212(1), pages 81-88, July.
    8. Wei, Cansheng & Li, Yongjian & Cai, Xiaoqiang, 2011. "Robust optimal policies of production and inventory with uncertain returns and demand," International Journal of Production Economics, Elsevier, vol. 134(2), pages 357-367, December.
    9. Kirlik, Gokhan & Sayın, Serpil, 2014. "A new algorithm for generating all nondominated solutions of multiobjective discrete optimization problems," European Journal of Operational Research, Elsevier, vol. 232(3), pages 479-488.
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