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Distribution planning for multi-echelon networks considering multiple sourcing and lateral transshipments
Authors:Mehdi Firoozi  M. Zied Babai  Walid Klibi  Yves Ducq
Affiliation:1. The Centre of Excellence in Supply Chain (CESIT), Kedge Business School, Bordeaux, France;2. University of Bordeaux, CNRS UMR 5218, IMS, Talence, Francemfiroozi@ompartners.com;4. Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT), Montreal, Canada;5. University of Bordeaux, CNRS UMR 5218, IMS, Talence, France
Abstract:Nowadays, due to the increasing complexity of business environment, especially demand uncertainty, supply chain managers need to establish more-effective sourcing and distribution strategies to ensure high customer service and low stock costs. To overcome this challenge multi-echelon network structures and alternative distribution strategies such as lateral transshipments and multiple sourcing should be considered in inventory optimisation models. In this article, we propose a scenario-based modelling approach to solve a two-stage multi-echelon inventory optimisation problem with a non-stationary demand. The model is based on a distribution requirements planning (DRP) approach and minimises the expected total cost that is composed of the fixed allocation, inventory holding, procurement, transportation, and back-ordering costs. Alternative inventory optimisation models, including the lateral transshipment strategy and multiple sourcing, are thus built, and the corresponding stochastic programmes are solved using the sample average approximation method. Through a numerical investigation conducted with several generated instances and an empirical investigation based on the case of a major French retailer’s distribution network, we show the substantial benefit of lateral transshipments and multiple sourcing in reducing the expected total costs of the distribution network.
Keywords:multi-echelon distribution networks  inventory optimisation  stochastic programming  lateral transshipment  multiple sourcing  non-stationary demand  DRP
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