A reformulation for the stochastic lot sizing problem with service-level constraints |
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Authors: | Huseyin Tunc Onur A Kilic S Armagan Tarim Burak Eksioglu |
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Institution: | 1. Institute of Population Studies, Hacettepe University, Ankara, Turkey;2. Department of Industrial and Systems Engineering, Mississippi State University, MS, United States |
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Abstract: | 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. |
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Keywords: | Stochastic lot sizing Reformulation Service level |
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