Fuzzy multicriteria analysis for performance evaluation of internet-of-things-based supply chains

Abstract

This paper presents a fuzzy multicriteria analysis model for evaluating the performance of Internet of Things (IoT)-based supply chains. The inherent uncertainty and imprecision of the performance evaluation process was handled by using intuitionistic fuzzy numbers. A new fuzzy multicriteria group decision making algorithm based on the technique ordered preference by similarity to the ideal solution (TOPSIS) approach, and the concept of similarity measures was developed for determining the overall performance of each alternative. The advantage of the proposed fuzzy multicriteria analysis model is that it can overcome the limitations of the existing approaches in an intuitionistic fuzzy environment. The fuzzy multicriteria group decision-making model provides organizations with the ability to evaluate the performance of their IoT-based supply chains for improving their competitiveness. An example is presented to highlight the usefulness of the proposed model for tackling a real world IoT performance evaluation problem.