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Record number 536156
Title Supply chain network design under uncertainty with evidence theory
Author(s) Samet, Ahmed; Bouzembrak, Yamine; Lefèvre, Eric
Source Logistics Research 10 (2017)1. - ISSN 1865-035X
Department(s) RIKILT - BU Toxicology Bioassays & Novel Foods
Publication type Refereed Article in a scientific journal
Publication year 2017
Keyword(s) BF-AHP - Evidence theory - Evidential data mining - Supply chain design - Two-stage stochastic programming
Abstract In this paper, we present a new approach to design a multi-criteria supply chain network (SCN) under uncertainty. Demands, supplies, production costs, transportation costs, opening costs are all considered as uncertain parameters. We propose an approach based on evidence theory (ET), analytic hierarchy process (AHP) and two-stage stochastic programming (TSSP). First, we integrate ET and AHP in order to include several criteria (social, economical, and environmental) and the uncertain experts decisions for selecting the best set of facilities. Second, we combine evidential data mining and TSSP approach: (i) to design the SCN, (ii) to take into account the uncertainty of supply chain parameters, and (iii) to reduce scenarios number by retaining only the significant ones. Finally, we illustrate the model with computational study to highlight the practicality and the efficiency of the proposed method.
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