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A heuristic approach for big bucket multi-level production planning problems

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  • AkartunalI, Kerem
  • Miller, Andrew J.
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    Abstract

    Multi-level production planning problems in which multiple items compete for the same resources frequently occur in practice, yet remain daunting in their difficulty to solve. In this paper, we propose a heuristic framework that can generate high quality feasible solutions quickly for various kinds of lot-sizing problems. In addition, unlike many other heuristics, it generates high quality lower bounds using strong formulations, and its simple scheme allows it to be easily implemented in the Xpress-Mosel modeling language. Extensive computational results from widely used test sets that include a variety of problems demonstrate the efficiency of the heuristic, particularly for challenging problems.

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    Bibliographic Info

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

    Volume (Year): 193 (2009)
    Issue (Month): 2 (March)
    Pages: 396-411

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    Handle: RePEc:eee:ejores:v:193:y:2009:i:2:p:396-411

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

    Related research

    Keywords: Integer programming Production planning Heuristics Relax-and-fix Strong formulations;

    References

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    1. MILLER, Andrew & NEMHAUSER, George & SAVELSBERGH, Martin, 2000. "Solving multi-item capacitated lot-sizing problems with setup times by branch-and-cut," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2000039, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. WOLSEY, Laurence, 2002. "Solving multi-item lot-sizing problems with an MIP solver using classification and reformulation," CORE Discussion Papers, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE) 2002012, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Michael Florian & Morton Klein, 1971. "Deterministic Production Planning with Concave Costs and Capacity Constraints," Management Science, INFORMS, INFORMS, vol. 18(1), pages 12-20, September.
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    6. Yves Pochet & Laurence A. Wolsey, 1991. "Solving Multi-Item Lot-Sizing Problems Using Strong Cutting Planes," Management Science, INFORMS, INFORMS, vol. 37(1), pages 53-67, January.
    7. Awi Federgruen & Michal Tzur, 1991. "A Simple Forward Algorithm to Solve General Dynamic Lot Sizing Models with n Periods in 0(n log n) or 0(n) Time," Management Science, INFORMS, INFORMS, vol. 37(8), pages 909-925, August.
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    12. Stadtler, Hartmut, 2003. "Multilevel lot sizing with setup times and multiple constrained resources: Internally rolling schedules with lot-sizing windows," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 20204, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    13. Horst Tempelmeier & Matthias Derstroff, 1996. "A Lagrangean-Based Heuristic for Dynamic Multilevel Multiitem Constrained Lotsizing with Setup Times," Management Science, INFORMS, INFORMS, vol. 42(5), pages 738-757, May.
    14. William W. Trigeiro & L. Joseph Thomas & John O. McClain, 1989. "Capacitated Lot Sizing with Setup Times," Management Science, INFORMS, INFORMS, vol. 35(3), pages 353-366, March.
    15. Gaetan Belvaux & Laurence A. Wolsey, 2001. "Modelling Practical Lot-Sizing Problems as Mixed-Integer Programs," Management Science, INFORMS, INFORMS, vol. 47(7), pages 993-1007, July.
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    Cited by:
    1. Wu, Tao & Shi, Leyuan & Geunes, Joseph & AkartunalI, Kerem, 2011. "An optimization framework for solving capacitated multi-level lot-sizing problems with backlogging," European Journal of Operational Research, Elsevier, Elsevier, vol. 214(2), pages 428-441, October.
    2. Lang, Jan Christian & Shen, Zuo-Jun Max, 2011. "Fix-and-optimize heuristics for capacitated lot-sizing with sequence-dependent setups and substitutions," European Journal of Operational Research, Elsevier, Elsevier, vol. 214(3), pages 595-605, November.

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