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An efficient computational method for a stochastic dynamic lot-sizing problem under service-level constraints

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Author Info

  • Tarim, S. Armagan
  • Dogru, Mustafa K.
  • Özen, Ulas
  • Rossi, Roberto
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    Abstract

    We provide an efficient computational approach to solve the mixed integer programming (MIP) model developed by Tarim and Kingsman [8] for solving a stochastic lot-sizing problem with service level constraints under the static-dynamic uncertainty strategy. The effectiveness of the proposed method hinges on three novelties: (i) the proposed relaxation is computationally efficient and provides an optimal solution most of the time, (ii) if the relaxation produces an infeasible solution, then this solution yields a tight lower bound for the optimal cost, and (iii) it can be modified easily to obtain a feasible solution, which yields an upper bound. In case of infeasibility, the relaxation approach is implemented at each node of the search tree in a branch-and-bound procedure to efficiently search for an optimal solution. Extensive numerical tests show that our method dominates the MIP solution approach and can handle real-life size problems in trivial time.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0377221711005637
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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 215 (2011)
    Issue (Month): 3 (December)
    Pages: 563-571

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    Handle: RePEc:eee:ejores:v:215:y:2011:i:3:p:563-571

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    Web page: http://www.elsevier.com/locate/eor

    Related research

    Keywords: Inventory Relaxation Stochastic non-stationary demand Mixed integer programming Service level Static-dynamic uncertainty;

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    Cited by:
    1. Tunc, Huseyin & Kilic, Onur A. & Tarim, S. Armagan & Eksioglu, Burak, 2013. "A simple approach for assessing the cost of system nervousness," International Journal of Production Economics, Elsevier, vol. 141(2), pages 619-625.

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