Open AccessDEVELOPMENT OF A NEW HYBRID MULTI CRITERIA DECISION-MAKING METHOD FOR A CAR SELECTION SCENARIO
Author(s) -
Yousaf Ali,
Bilal Mehmood,
Muhammad Huzaifa,
Umair Yasir,
Amin Ullah Khan
Publication year - 2020
Publication title -
facta universitatis. series: mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.483
H-Index - 16
eISSN - 2335-0164
pISSN - 0354-2025
DOI - 10.22190/fume200305031a
Subject(s) - topsis , ranking (information retrieval) , selection (genetic algorithm) , consistency (knowledge bases) , analytic hierarchy process , rank (graph theory) , computer science , multiple criteria decision analysis , operations research , process (computing) , fuzzy logic , novelty , variety (cybernetics) , engineering , mathematics , artificial intelligence , philosophy , theology , combinatorics , operating system
Increasing competition in the automobile industry has led to a vast variety of choices when buying a car thus making car selection a tedious task. The objective of this research is to develop a new hybrid multi-criteria decision-making technique, with accuracy greater than that of the already existing methods, in order to help the people in decision-making while buying a car. Hence, considering a broader spectrum, this study aims at easing the process of multi-criteria decision-making problems in different fields. To achieve the objective, seven different alternatives were evaluated with respect to the enlisted evaluation criteria, which were selected after analyzing the secondary data obtained from Pak wheels based on style, fuel economy, price, comfort and performance. These criteria were then analyzed using the proposed Full Consistency Fuzzy TOPSIS method. As the name tells, this method is a unique combination of two techniques. The Full Consistency method is used to calculate the weights of the criteria while the Fuzzy TOPSIS approach is applied to rank the alternatives according to their scores in the selected criteria. The outcomes demonstrate an increase in the consistency ratio of the weight coefficients due to which the ranking of the alternatives by the FCF-TOPSIS is more accurate than the TOPSIS and the Analytical Hierarchy Process. The novelty of the method lies in the fact that this combination has not been used for an alternative selection scenario before. In addition to this, it can be used in various industries where a choice between the available alternatives arises based on a set of evaluation criteria.