SELECTION OF CAR USING FUZZY AHP AND FUZZY TOPSIS METHOD BY MCDM APPROACH

Using Multi Criteria Decision Making Tools

Abstract

With the automotive industry offering diverse vehicles to cater to various needs, selecting the ideal car becomes challenging. The study highlights the rising significance of cars as a necessity, exemplified by India's car ownership rate. The paper employs a Multi-Criteria Decision-Making (MCDM) approach, focusing on cost, safety, comfort, and performance, with 14 sub-criteria, for a comprehensive evaluation structure.

The research employs Fuzzy AHP and Fuzzy TOPSIS methods to handle the uncertainties inherent in decision-making processes. These techniques integrate fuzzy set theory to realistically capture real-world complexities. The goal is to systematically evaluate and choose cars based on individual preferences and priorities. The findings reveal that Alternative A (SWIFT) is the optimal choice among evaluated options like BALENO, NEXON, and HARRIER. Both consumer preferences and expert opinions align in favor of SWIFT. The Fuzzy Analytical Hierarchy Process (FAHP) confirms SWIFT's excellence across criteria.

Additionally, the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS) solidifies this conclusion. FTOPSIS demonstrates SWIFT's minimal deviation from the positive ideal solution and significant separation from the negative ideal solution. Calculated CCi values rank SWIFT as the top choice, followed by BALENO, NEXON, and HARRIER. The paper's significance lies in providing potential car buyers with an informed decision-making framework to navigate the overwhelming car market. By combining fuzzy sets with established MCDM methods, the research enhances decision-making accuracy. The study contributes to MCDM knowledge and practical car selection insights, benefiting both consumers and the industry. Ultimately, the study reinforces SWIFT's superiority across cost, safety, comfort, and performance domains, demonstrating the effectiveness of the MCDM approach in complex decision scenarios