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Single-Stage Resource Allocation and Economic Lot Scheduling on Multiple, Nonidentical Production Lines


Author Info

  • Ramesh Bollapragada

    (Bell Laboratories, Lucent Technologies, Room 2L-515, 101 Crawfords Corner Road, Holmdel, New Jersey 07733)

  • Uday Rao

    (Graduate School of Industrial Administration, Carnegie-Mellon University, Pittsburgh, Pennsylvania 15213)

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    This paper focuses on simultaneous resource allocation, lot-sizing, and scheduling in a multimachine, deterministic ELSP environment. We consider the problem of apportioning item production to distinct manufacturing lines with different costs and capabilities (production rates). The objective is to minimize the long-run average production, setup, inventory, and shortage penalty costs (due to lost sales). Restricting attention to rotation schedules, we develop a concave minimization model of the problem, generate heuristic solutions and a lower bound on the cost of any feasible solution. Computational experiments indicate that our heuristic solution is within a few percent of the lower bound. We also investigate sensitivity of costs to model parameters, and illustrate how our model may be used to determine target values for equipment utilization.

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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 45 (1999)
    Issue (Month): 6 (June)
    Pages: 889-904

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    Handle: RePEc:inm:ormnsc:v:45:y:1999:i:6:p:889-904

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    Keywords: lot-sizing; scheduling; resource allocation;


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    Cited by:
    1. Torabi, S.A. & Karimi, B. & Fatemi Ghomi, S.M.T., 2005. "The common cycle economic lot scheduling in flexible job shops: The finite horizon case," International Journal of Production Economics, Elsevier, vol. 97(1), pages 52-65, July.
    2. Teunter, Ruud & Kaparis, Konstantinos & Tang, Ou, 2008. "Multi-product economic lot scheduling problem with separate production lines for manufacturing and remanufacturing," European Journal of Operational Research, Elsevier, vol. 191(3), pages 1241-1253, December.


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