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2531. Multi-stage Stochastic Programming for Lot Sizing with Perishables under Demand Substitution
Invited abstract in session TA-49: Stochastic lot-sizing problems, stream Lot Sizing, Lot Scheduling and Production Planning.
Tuesday, 8:30-10:00Room: M1 (building: 101)
Authors (first author is the speaker)
| 1. | Bahar Cennet Okumusoglu
|
| TUM School of Management, Technical University of Munich | |
| 2. | Martin Grunow
|
| TUM School of Management, Technical University of Munich |
Abstract
For perishable products, it is common industry practice to resort to substitution in case of stock-outs. In this work, we investigate the stochastic capacitated lot-sizing problem for perishable products under dynamic demand substitution. We consider a single-echelon lot-sizing setting with multiple products that require the same limited production capacity. We assume that products have fixed shelf-lives and constant production lead times. To represent real-life conditions, we allow for correlated product demands that evolve dynamically over time. We formulate this problem as a multi-stage stochastic program and propose a scenario tree approximation. We solve the resulting problem in a rolling horizon procedure. Our preliminary numerical results demonstrate the value of our proposed formulation for production and inventory planning of perishables and the value of substitution.
Keywords
- Supply Chain Management
- Programming, Stochastic
Status: accepted
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