Supply chain network design under uncertainty with evidence theory

Ahmed Samet*, Yamine Bouzembrak, Eric Lefèvre

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


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.
Original languageEnglish
Article number8
JournalLogistics Research
Issue number1
Publication statusPublished - 1 Dec 2017


  • BF-AHP
  • Evidence theory
  • Evidential data mining
  • Supply chain design
  • Two-stage stochastic programming

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