
Least to Most Range (LMR): A novel consistent weighting multicriteria method applied to Green Supplier Selection
Author(s) -
Vinicius Moretti,
Everton L. Melo,
Joao Carlos Colmenero
Publication year - 2025
Publication title -
ieee access
Language(s) - English
Resource type - Magazines
SCImago Journal Rank - 0.587
H-Index - 127
eISSN - 2169-3536
DOI - 10.1109/access.2025.3596799
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Decision-making is a complex task for people, professionally or personally, since the decision has several positive and negative consequences and cannot always be undone. Multicriteria decision-making models (MCDM) aim to reduce the complexity of decision-making by using mathematical and algorithmic procedures to guide the process. Given the various issues and complexities that current methods for weighting criteria present; this study aims to develop a new subjective multicriteria method for criteria weighting applied in Green Supplier Selection (GSS). To solve this GSS problem, the Least to Most Range (LMR) method was developed and applied. The LMR is characterized by presenting a new logic for weighting criteria using two distinct and complementary scales. This method has a series of advantages over some well-established methods in the literature, and to illustrate these advantages, a numerical application was developed in GSS containing a literature review to survey relevant criteria for the problem. The LMR has proven robust compared to other methods because it can treat many criteria simultaneously without presenting inconsistency, satisfactorily dealing with some of the problems most commonly found in weighting methods in the literature.
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