Determining weights of fuzzy attributes for multi-attribute decision-making problems based on consensus of expert opinions

Seyed Hossein Razavi Hajiagha, Hannan Amoozad Mahdiraji, Shide Sadat Hashemi, Zenonas Turskis

Research output: Contribution to journalArticle

16 Citations (Scopus)
7 Downloads (Pure)

Abstract

An important objective of a group decision-making problem is to determine the weights of attributes that are given by experts participating in the decision-making process. Since different
decision-makers have unequal importance in decision-making, a series of studies focused on finding a set of appropriate weights for experts participating in a decision problem. In this paper, the
problem of weight determination among decision-makers is investigated by extending an algorithm taken from the technique for order preference by similarity-to-ideal solution. In this case, a pair of most compromising and least compromising solutions is derived from individual judgments of decision-makers and then, these solutions are applied as the bases for determining the magnitude of individual alignment with the group opinion by using a closeness coefficient approach. Determining the weights of decision-makers, the group decision-making problem is then solved. Application of the proposed method is illustrated by a numerical example for the selection of a maintenance
strategy.
Original languageEnglish
Pages (from-to)738-755
Number of pages18
JournalTechnological and Economic Development of Economy
Volume21
Issue number5
DOIs
Publication statusPublished - 3 Sep 2015
Externally publishedYes

Bibliographical note

Copyright © 2019 The Author(s). Published by VGTU Press.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Keywords

  • weights
  • multi-attribute
  • fuzzy
  • group decision-making
  • linguistic variable
  • Triangular fuzzy numbers
  • most compromising solution
  • least compromising solution

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