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Lot Sizing in General Assembly Systems with Setup Costs, Setup Times, and Multiple Constrained Resources


Author Info

  • Elena Katok

    (Division of Economics and Business, Colorado School of Mines, Golden, Colorado 80401)

  • Holly S. Lewis

    (Department of Management Science and Information Systems, The Pennsylvania State University, University Park, Pennsylvania 16802)

  • Terry P. Harrison

    (Department of Management Science and Information Systems, The Pennsylvania State University, University Park, Pennsylvania 16802)


We introduce a heuristic method for finding good, feasible solutions for multiproduct lot sizing problems with general assembly structures, multiple constrained resources, and nonzero setup costs and setup times. We evaluate the performance of this heuristic by comparing its solutions to optimal solutions of small randomly generated problems and to time-truncated Optimization Subroutine Library (OSL) solutions of medium-sized randomly generated problems. In the first case, the heuristic locates solutions averaging 4 percent worse than optimal in less than 1 percent of time required by OSL. The heuristic solutions to medium-sized problems are approximately 26 percent better than solutions OSL finds after 10,000 CPU seconds, and the heuristic finds these solutions in approximately 10 percent of OSL time.

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Bibliographic Info

Article provided by INFORMS in its journal Management Science.

Volume (Year): 44 (1998)
Issue (Month): 6 (June)
Pages: 859-877

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Handle: RePEc:inm:ormnsc:v:44:y:1998:i:6:p:859-877

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Related research

Keywords: Lot Sizing; General Assembly System; Heuristics; Integer Programming;

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Cited by:
  1. Süral, Haldun & Denizel, Meltem & Van Wassenhove, Luk N., 2009. "Lagrangean relaxation based heuristics for lot sizing with setup times," European Journal of Operational Research, Elsevier, vol. 194(1), pages 51-63, April.
  2. BELVAUX, Gaetan & WOLSEY, Laurence A., 1998. "Lot-sizing problems: modelling issues and a specialized branch-and-cut system BC-PROD," CORE Discussion Papers 1998049, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  3. Jans, Raf & Degraeve, Zeger, 2007. "Meta-heuristics for dynamic lot sizing: A review and comparison of solution approaches," European Journal of Operational Research, Elsevier, vol. 177(3), pages 1855-1875, March.
  4. Sahling, Florian & Buschkühl, Lisbeth & Tempelmeier, Horst & Helber, Stefan, 2008. "Solving a Multi-Level Capacitated Lot Sizing Problem with Multi-Period Setup Carry-Over via a Fix-and-Optimize Heuristic," Hannover Economic Papers (HEP) dp-400, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  5. Helber, Stefan & Sahling, Florian, 2008. "A Fix-and-Optimize Approach for the Multi-Level Capacitated Lot Sizing Problems," Hannover Economic Papers (HEP) dp-393, Leibniz Universität Hannover, Wirtschaftswissenschaftliche Fakultät.
  6. AkartunalI, Kerem & Miller, Andrew J., 2009. "A heuristic approach for big bucket multi-level production planning problems," European Journal of Operational Research, Elsevier, vol. 193(2), pages 396-411, March.
  7. Berretta, Regina & Rodrigues, Luiz Fernando, 2004. "A memetic algorithm for a multistage capacitated lot-sizing problem," International Journal of Production Economics, Elsevier, vol. 87(1), pages 67-81, January.
  8. Brahimi, Nadjib & Dauzere-Peres, Stephane & Najid, Najib M. & Nordli, Atle, 2006. "Single item lot sizing problems," European Journal of Operational Research, Elsevier, vol. 168(1), pages 1-16, January.
  9. VAN VYVE, Mathieu & POCHET, Yves, 2001. "A general heuristic or production planning problems," CORE Discussion Papers 2001056, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  10. Sarker, Bhaba R. & Diponegoro, Ahmad, 2009. "Optimal production plans and shipment schedules in a supply-chain system with multiple suppliers and multiple buyers," European Journal of Operational Research, Elsevier, vol. 194(3), pages 753-773, May.


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