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Supply chain network design with unreliable suppliers: a Lagrangian relaxation-based approach
Authors:Lyes Benyoucef  Xiaolan Xie  Guy Aime Tanonkou
Affiliation:1. Aix-Marseille University, LSIS UMR 7296, Marseille, France.lyes.benyoucef@lsis.org;3. ENSM.SE, Engineering and Heath Division, Saint-Etienne, France.;4. Department of Industrial Engineering and Logistics Management, Shanghai Jiao Tong University, Shanghai, P.R. China.;5. Faculty of Sciences, Technology and Communication, University of Luxembourg, Luxembourg City, Luxembourg.
Abstract:This paper deals with the integrated facility location and supplier selection decisions for the design of supply chain network with reliable and unreliable suppliers. Two problems are addressed: (1) facility location/supplier selection; and (2) facility location/supplier reliability. We first consider the facility location and supplier selections problem where all the suppliers are reliable. The decisions concern the selection of suppliers, the location of distribution centres (DCs), the allocation of suppliers to DCs and the allocation of retailers to DCs. The objective is to minimise fixed DCs location costs, inventory and safety stock costs at the DCs and ordering costs and transportation costs across the network. The introduction of inventory costs and safety stock costs leads to a non-linear NP-hard optimisation problem. To solve this problem, a Lagrangian relaxation-based approach is developed. For the second problem, a two-period decision model is proposed in which selected suppliers are reliable in the first period and can fail in the second period. The corresponding facility location/supplier reliability problem is formulated as a non-linear stochastic programming problem. A Monte Carlo optimisation approach combining the sample average approximation scheme and the Lagrangian relaxation-based approach is proposed. Computational results are presented to evaluate the efficiency of the proposed approaches.
Keywords:supply chain  facility location  supplier selection  reliability  optimisation  Lagrangian relaxation  sample average approximation
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