A Pythagorean cubic fuzzy methodology based on TOPSIS and TODIM methods and its application to software selection problem

Software selection process for many organizations is a challenging task to conduct their business activities and sustain competitiveness. This paper develops a new hybrid multi-criteria decision-making (MCDM) method to select the most efficient vendor-supplied software package which is used in all b...

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Vydané v:Soft computing (Berlin, Germany) Ročník 26; číslo 5; s. 2437 - 2450
Hlavní autori: Seker, Sukran, Kahraman, Cengiz
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2022
Predmet:
Artificial Intelligence
Computational Intelligence
Control
Engineering
Mathematical Logic and Foundations
Mechatronics
Robotics
Soft Computing in Decision Making and in Modeling in Economics
TODIM
Software selection
MCDM
TOPSIS
Pythagorean cubic fuzzy sets
ISSN:1432-7643, 1433-7479
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Shrnutí:Software selection process for many organizations is a challenging task to conduct their business activities and sustain competitiveness. This paper develops a new hybrid multi-criteria decision-making (MCDM) method to select the most efficient vendor-supplied software package which is used in all business activities for planning or designing, organizing, and supervising functions by operations management of a fuel oil company operated in Turkey. The proposed method is a hybridization of two well-known MCDM approaches, namely TODIM (an acronym in Portuguese for interactive and multi-criteria decision making) and TOPSIS (technique for order preference by similarity to an ideal solution) using Pythagorean cubic fuzzy sets to manage uncertainty, subjectivity and bias of decision makers. To prove the efficiency and applicability of the proposed method, a real-life application to select best software package for fuel oil company is conducted. Finally, sensitivity and comparison analyses are carried out to verify validity and stability of the results obtained by the proposed approach.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-021-06469-8