On SIR-based MCDM approach: Selecting a charcoal firm using hybrid fuzzy number on a Triple Vague structure.

Heliyon

Department of Mathematics, School of Advanced Sciences, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India.

Published: January 2024

Multi-Criteria Decision Making (MCDM) is a widely used method across various sectors to help decision-makers assess and choose the most suitable solutions from a range of available options. This research introduces an innovative framework called the Triple Vague (TV) structure for Superiority and Inferiority Ranking (SIR) within the context of MCDM. This framework incorporates interval fuzzy numbers and hesitant fuzzy numbers, including negative interval fuzzy numbers for different vague ideas. The main goal of this research is to present an effective solution to the challenge of selecting a firm, specifically focusing on the manufacturing of charcoal from waste coconut shells. The SIR approach is employed to establish two complete rankings, and a TV value is used to articulate the assessment information. In this article, our contribution lies in the proposed Triple Vague approach, which utilizes the superiority and inferiority ranking methodology to identify the best firm for charcoal manufacturing. Further, it demonstrates through an application example involving the selection of the most suitable firm among four different options based on specified criteria for charcoal production from coconut shell waste. Also, comparative analysis has been done with other MCDM methods like TOPSIS, Grey method and PROMETHEE method. This analysis examines that the proposed structure is better than other MCDM technique. Moreover, the results highlight the framework's capability to handle the hesitation, vagueness, and like other undesirable characteristics. Hence it provides valuable insights for decision-makers to thoroughly evaluate and consider the best alternatives.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10826662PMC
http://dx.doi.org/10.1016/j.heliyon.2024.e24248DOI Listing

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