Fuzzy multi-objective optimization for network design of integrated e-supply chains

Worldwide competition originated the development of integrated e-supply chains (IESC) that are distributed manufacturing systems integrating international logistics and information technologies with production. This work builds upon an IESC network design methodology previously proposed to select partners in the different IESC stages and the links connecting them. In order to rank the Pareto optimal solutions obtained by such a method, the paper proposes a second level IESC optimization performed using fuzzy logic. Indeed, fuzzy multi-criteria optimization is particularly suitable for choosing, on the basis of the subjective and qualitative knowledge provided by the decision makers, the IESC configuration from the set of Pareto optimal alternatives. Two fuzzification techniques and two different multi-criteria methods are considered. Moreover, a discussion on the different advantages and limitations of the proposed techniques is provided. Finally, the effectiveness of the methodology is illustrated by way of a case study.