Open Access

ARTICLE

A New Decision-Making Model Based on Plithogenic Set for Supplier Selection

by Mohamed Abdel-Basset^1,*, Rehab Mohamed¹, Florentin Smarandache², Mohamed Elhoseny³

1 Faculty of Computers and Informatics, Zagazig University, Zagazig, 44519, Egypt
2 Math & Science Department, University of New Mexico, Gallup, New Mexico, 87301, USA
3 College of Computer Information Technology, American University in the Emirates, Dubai, The United Arab Emirates

* Corresponding Author: Mohamed Abdel-Basset. Email:

(This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)

Computers, Materials & Continua 2021, 66(3), 2751-2769. https://doi.org/10.32604/cmc.2021.013092

Received 25 July 2020; Accepted 21 September 2020; Issue published 28 December 2020

Abstract

Supplier selection is a common and relevant phase to initialize the supply chain processes and ensure its sustainability. The choice of supplier is a multi-criteria decision making (MCDM) to obtain the optimal decision based on a group of criteria. The health care sector faces several types of problems, and one of the most important is selecting an appropriate supplier that fits the desired performance level. The development of service/product quality in health care facilities in a country will improve the quality of the life of its population. This paper proposes an integrated multi-attribute border approximation area comparison (MABAC) based on the best-worst method (BWM), plithogenic set, and rough numbers. BWM is applied to regulate the weight vector of the measures in group decision-making problems with a high level of consistency. For the treatment of uncertainty, a plithogenic set and rough number (RN) are used to improve the accuracy of results. Plithogenic set operations are used to deal with information in the desired manner that handles uncertainty and vagueness. Then, based on the plithogenic aggregation and the results of BWM evaluation, we use MABAC to find the optimal alternative according to defined criteria. To examine the proposed integrated algorithm, an empirical example is produced to select an optimal supplier within five options in the healthcare industry.

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