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A Lagrangian Relaxation approach for production planning with demand uncertainty

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  • Haoxun Chen
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    Abstract

    A production planning problem with stochastic demands is considered in this paper. The problem is to determine over a given time horizon the production quantity of each intermediate/final product at each facility of finite capacity so that a system-wide total cost is minimised while meeting given service level requirements for the final products. After reformulating the stochastic decision problem as a multiitem, multistage capacitated lot-sizing problem with a non-linear cost function using deterministic equivalence, it is solved by using a Lagrangian Relaxation (LR) approach enhanced with a local search method based on a modified simplex algorithm. Numerical experiments show that the approach can find high quality near-optimal solutions for randomly generated problems of realistic sizes in a computation time much shorter than that of an exact algorithm. [Received on 2 February 2007; Revised 28 May 2007; Accepted 7 June 2007]

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    Bibliographic Info

    Article provided by Inderscience Enterprises Ltd in its journal European J. of Industrial Engineering.

    Volume (Year): 1 (2007)
    Issue (Month): 4 ()
    Pages: 370-390

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    Handle: RePEc:ids:eujine:v:1:y:2007:i:4:p:370-390

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    Web page: http://www.inderscience.com/browse/index.php?journalID=210

    Related research

    Keywords: production planning; lot sizing; demand uncertainty; Lagrangian relaxation; local search.;

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