Designing a Two-Echelon Distribution Network under Demand Uncertainty
hal.structure.identifier | Reformulations based algorithms for Combinatorial Optimization [Realopt] | |
hal.structure.identifier | Kedge Business School [Talence] | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
dc.contributor.author | BEN MOHAMED, Imen | |
hal.structure.identifier | Centre Interuniversitaire de Recherche sur les Réseaux d'Entreprise, la Logistique et le Transport [CIRRELT] | |
hal.structure.identifier | Kedge Business School [Talence] | |
dc.contributor.author | KLIBI, Walid | |
hal.structure.identifier | Institut de Mathématiques de Bordeaux [IMB] | |
hal.structure.identifier | Reformulations based algorithms for Combinatorial Optimization [Realopt] | |
dc.contributor.author | VANDERBECK, François | |
dc.date | 2019 | |
dc.date.accessioned | 2024-04-04T03:00:37Z | |
dc.date.available | 2024-04-04T03:00:37Z | |
dc.date.issued | 2019 | |
dc.identifier.issn | 0377-2217 | |
dc.identifier.uri | https://oskar-bordeaux.fr/handle/20.500.12278/192832 | |
dc.description.abstractEn | This paper proposes a comprehensive methodology for the stochastic multi-period two-echelon distribution network design problem (2E-DDP) where product flows to ship-to-points are directed from an upper layer of primary warehouses to distribution platforms (DPs) before being transported to the ship-to-points. A temporal hierarchy characterizes the design level dealing with DP location and capacity decisions, as well as the operational level involving transportation decisions as origin-destination flows. These design decisions must be calibrated to minimize the expected distribution cost associated with the two-echelon transportation schema on this network under stochastic demand. We consider a multi-period planning horizon where demand varies dynamically from one planning period to the next. Thus, the design of the two-echelon distribution network under uncertain customer demand gives rise to a complex multi-stage decisional problem. Given the strategic structure of the problem, we introduce alternative modeling approaches based on two-stage stochastic programming with recourse. We solve the resulting models using a Benders decomposition approach. The size of the scenario set is tuned using the sample average approximation (SAA) approach. Then, a scenario-based evaluation procedure is introduced to post-evaluate the design solutions obtained. We conduct extensive computational experiments based on several types of instances to validate the proposed models and assess the efficiency of the solution approaches. The evaluation of the quality of the stochastic solution underlines the impact of uncertainty in the two-echelon distribution network design problem (2E-DDP). | |
dc.language.iso | en | |
dc.publisher | Elsevier | |
dc.subject.en | Location models | |
dc.subject.en | Multi-period | |
dc.subject.en | Uncertainty | |
dc.subject.en | Supply chain management | |
dc.subject.en | Two-echelon Distribution Network Design | |
dc.title.en | Designing a Two-Echelon Distribution Network under Demand Uncertainty | |
dc.type | Article de revue | |
dc.identifier.doi | 10.1016/j.ejor.2019.06.047 | |
dc.subject.hal | Informatique [cs]/Recherche opérationnelle [cs.RO] | |
bordeaux.journal | European Journal of Operational Research | |
bordeaux.page | 102-123 | |
bordeaux.volume | 280 | |
bordeaux.hal.laboratories | Institut de Mathématiques de Bordeaux (IMB) - UMR 5251 | * |
bordeaux.issue | 1 | |
bordeaux.institution | Université de Bordeaux | |
bordeaux.institution | Bordeaux INP | |
bordeaux.institution | CNRS | |
bordeaux.peerReviewed | oui | |
hal.identifier | hal-02167587 | |
hal.version | 1 | |
hal.popular | non | |
hal.audience | Internationale | |
hal.origin.link | https://hal.archives-ouvertes.fr//hal-02167587v1 | |
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