Published January 1, 2014 | Version v1
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A reformulation for the stochastic lot sizing problem with service-level constraints

  • 1. Hacettepe Univ, Inst Populat Studies, Ankara, Turkey
  • 2. Mississippi State Univ, Dept Ind & Syst Engn, Mississippi State, MS USA

Description

We study the stochastic lot-sizing problem with service level constraints and propose an efficient mixed integer reformulation thereof. We use the formulation of the problem present in the literature as a benchmark, and prove that the reformulation has a stronger linear relaxation. Also, we numerically illustrate that it yields a superior computational performance. The results of our numerical study reveals that the reformulation can optimally solve problem instances with planning horizons over 200 periods in less than a minute. (C) 2014 Elsevier B.V. All rights reserved.

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