
handle: 10419/182053
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, eco- nomical, 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.
Supply chain design, Two-stage Stochastic Programming, Two-stage stochastic programming, Industries. Land use. Labor, ddc:650, HD28-9999, Evidential data mining, Transportation and communications, BF-AHP, Evidence theory, HE1-9990
Supply chain design, Two-stage Stochastic Programming, Two-stage stochastic programming, Industries. Land use. Labor, ddc:650, HD28-9999, Evidential data mining, Transportation and communications, BF-AHP, Evidence theory, HE1-9990
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
