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Modeling and solving a distribution network design problem with multiple operational constraints. Application to a case-study in the automotive industry.

Abstract : Facility location and network design theories have been widely studied by OR researchers during the last decades. This interest might be explained by the strategic importance of these problems for industrial companies as well as by the research challenges to be tackled to model and solve them. Although real-life case-studies reported in the academic literature are rather scarce, several recent works have focused on improving the practical relevance of facility location models by considering operational features. The purpose of our research project is to develop a distribution network design model taking into account many realistic features arising from a case-study in the field of car distribution. Our modeling choices were motivated by our practical application but can be relevant in other industrial contexts. The overall network structure consists of three levels: plants in the fi rst level, distribution centres (DCs) in the second one and customers in the third one. We assume that the number and location of the plants as well as the number and location of the customers are fixed. Given the demand of customers and a list of potential DCs, our main concern is to locate DCs and to assign customers to them in such a way as to minimize the total distribution costs. Our contributions relate to the modeling of a real-life problem, the development of e fficient solution methods and the analysis of the obtained numerical results. In terms of problem modeling, we integrate various operational features that were considered separately in the literature but have never been combined in a same model. Namely, we introduce a clustering-based approach to model vehicle routing, minimum volume constraints to ensure full truckload transport, minimum and maximum throughput constraints on DCs, maximum covering distance constraints and single sourcing restrictions. Furthermore, we study a multi-period extension of the problem using an original dynamic clustering to model multi-period vehicle routing. In terms of solution method, as the problem we study is NP-Hard in the strong sense, we propose effi cient heuristic procedures based on various types of linear relaxation. Through our numerical experiments, we show that the implemented heuristics off er near-optimal solutions with less computational e ffort than applying an exact MIP solver. We also analyze the structure of the obtained networks and compare the results of several versions of the model, highlighting the value of integrating a pre-processing clustering step and of using a multi-period approach.
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Submitted on : Friday, February 14, 2014 - 12:13:47 PM
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Mouna Kchaou-Boujelben. Modeling and solving a distribution network design problem with multiple operational constraints. Application to a case-study in the automotive industry.. Operations Research [cs.RO]. Ecole Centrale Paris, 2013. English. ⟨tel-00946890⟩

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