Tight Mip Formulation for Multi-Item Discrete Lot-Sizing Problems

Andrew J. Miller () and Laurence A. Wolsey ()
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Andrew J. Miller: Department of Industrial Engineering, University of Wisconsin at Madison, Madison, Wisconsin 53706
Laurence A. Wolsey: CORE and INMA, Université Catholique de Louvain, 1348 Louvain-la-Neuve, Belgium

Operations Research, 2003, vol. 51, issue 4, 557-565

Abstract: This paper discusses mixed-integer programming formulations of variants of the discrete lot-sizing problem. Our approach is to identify simple mixed-integer sets within these models and to apply tight formulations for these sets. This allows us to define integral linear programming formulations for the discrete lot-sizing problem in which backlogging and/or safety stocks are present, and to give extended formulations for other cases. The results help significantly to solve test cases arising from an industrial application motivating this research.

Keywords: Inventory/production: scale-diseconomies/lot-sizing; discrete lot-sizing; Production/scheduling: planning; Integer programming: convex integer programming; facets; extended formulations (search for similar items in EconPapers)
Date: 2003
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Citations: View citations in EconPapers (7)

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