A fuzzy parametric model for decision making involving F-OWA operator with unknown weights environment

Muhammad Touqeer; Saleh Al Sulaie; Showkat Ahmad Lone; Kiran Shaheen; Nevine M Gunaime; Mohamed Abdelghany Elkotb

doi:10.1016/j.heliyon.2023.e19969

A fuzzy parametric model for decision making involving F-OWA operator with unknown weights environment

Heliyon. 2023 Sep 12;9(9):e19969. doi: 10.1016/j.heliyon.2023.e19969. eCollection 2023 Sep.

Authors

Muhammad Touqeer¹, Saleh Al Sulaie², Showkat Ahmad Lone³, Kiran Shaheen¹, Nevine M Gunaime³, Mohamed Abdelghany Elkotb⁴

Affiliations

¹ Department of Basic Sciences, University of Engineering and Technology, Taxila 47050, Pakistan.
² Department of Industrial Engineering, College of Engineering in Al-Qunfudah, Umm Al-Qura University, Makkah 21955, Saudi Arabia.
³ Department of Basic Sciences, College of Science and Theoretical Studies, Saudi Electronic University, Riyadh 11673, Kingdom of Saudi Arabia.
⁴ Mechanical Engineering Department, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia.

Abstract

Weight determining of attributes is an important factor in decision support systems since it corresponds to the relative importance of each criteria which is necessary to be determined since all the attributes aren't equally important. The aim of this paper is to put forward a method for multi Criteria decision making (MCDM) problems based on three trapezoidal fuzzy numbers under completely unknown weights environment. Based on the idea that the attribute with a larger deviation value among alternatives should be assigned a larger weight, an optimization model based on maximizing deviation method is established. F-OWA is considered to be vastly superior from the existing operators which usually take into account only the relative significance of decision makers. F-OWA operator considers not only the ratings of attribute values but also their ordered position that is it not only signifies the decision makers but also values the individual assessments. We utilize fuzzy ordered weighted averaging (F-OWA) operator to compute the collective overall preference value of each alternative and select the most desirable one according to their expected score values. The presented method is more generalized since we have used TTFNs, which are more effective in capturing uncertainty than IT2FS, just like triangular fuzzy numbers have a better representational power than simple interval numbers. Moreover, an illustrative example is given for the justification of the proposed technique.

Keywords: Fuzzy ordered weighted averaging (F-OWA); Linguistic variables; Maximizing deviation; Three trapezoidal fuzzy numbers (TTFNs).