Wibowo, S.; Grandhi, S. Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains. Symmetry2018, 10, 603.
Wibowo, S.; Grandhi, S. Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains. Symmetry 2018, 10, 603.
Wibowo, S.; Grandhi, S. Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains. Symmetry2018, 10, 603.
Wibowo, S.; Grandhi, S. Fuzzy Multicriteria Analysis for Performance Evaluation of Internet-of-Things-Based Supply Chains. Symmetry 2018, 10, 603.
Abstract
The performance evaluation of the Internet of Things (IoT) based supply chain is challenging due to the involvement of multiple decision makers, the multi-dimensional nature of the evaluation process, and the existence of uncertainty and imprecision in the decision making process. To ensure effective decisions are made, this paper presents a fuzzy multicriteria analysis model for evaluating the performance of IoT based supply chain. The inherent uncertainty and imprecision of the performance evaluation process is adequately handled by using intuitionistic fuzzy numbers. A new algorithm is developed for determining the overall performance index for each alternative across all criteria. The development of the fuzzy multicriteria group decision making model provides organizations with the ability to effectively evaluate the performance of their IoT based supply chains for improving their competitiveness. An example is presented for demonstrating the applicability of the model for dealing with real world IoT-based performance evaluation problems.
Keywords
group decision makers; multicriteria analysis; performance evaluation; internet of things; intuitionistic environment
Subject
Computer Science and Mathematics, Computer Networks and Communications
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.