The COVID 19 pandemic, fluctuating demand, market uncertainty and the emergence of new technologies explain the need for a more flexible and agile supply chain. In fact, several important factors should be taken into account in the process of building an adaptive and reconfigurable supply chain. Reconfigurability is used to measure quantitatively the capability of supply chain to change easily their structure and functions. The aim of this work is to evaluate the level of reconfigurability of a supply chain. Quantitative measures of six indicators that characterize reconfigurability are presented in this paper. Then, an index of reconfigurability in supply chain is developed based on The Multi-Attribute Utility Theory in order to choose the most reconfigurable configuration. An illustrative example is also given. From the discussion, it is deduced that the characteristics of the reconfigurable supply chain impacts positively on the degree of reconfigurability.

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The purpose of this paper is to help decision-makers choose the location of a logistics platform with sustainability perspectives. This study presents a compensatory and partially compensatory approach to build composite indicators, using mainly fuzzy multi-criteria decision-making methods. In the first instance, the fuzzy full consistency method (F-FUCOM) was used to calculate the weight of the criteria and sub-criteria. In the second instance, two aggregation methods, namely the fuzzy multi-attribute ideal-real comparative analysis (F-MAIRCA) and the fuzzy preference ranking organization method for enrichment evaluation (F-PROMETHEE), were used to rank the location of a logistics platform. The novelty of the work lays in studying the impact of limited sustainability and weak sustainability on the location of a logistics platform. In this respect, the aggregation of various sustainability criterion in fuzzy compensatory and partially compensatory composite indicators is an innovative and interesting approach used to locate a logistics platform. The obtained results show that economic sustainability is the most important criterion for the selection of a logistics platform, followed by the environmental criterion. Obviously, the F-MAIRCA and F-PROMETHEE methods provided the same ranking orders. Finally, sensitivity analyses were performed to validate the robustness of the proposed approach.