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A Study on the Efficiency of Divergence Measure in Fuzzy TOPSIS Algorithm for Multi-attribute Decision Making—A Case Study on University Selection for Admission

Author

Listed:
  • Mansi Bhatia

    (Amity Institute of Applied Sciences, Amity University Uttar Pradesh)

  • H. D. Arora

    (Amity Institute of Applied Sciences, Amity University Uttar Pradesh)

  • Riju Chaudhary

    (Amity Institute of Applied Sciences, Amity University Uttar Pradesh)

  • Vijay Kumar

    (Manav Rachna International Institute of Research and Studies)

Abstract

In our daily lives, individuals face countless choices across different aspects. Many a times these decisions are made based on a number of factors, some of which are obvious, whereas some of them are vague and not precise. These can result in facing certain challenges while making decisions. To handle such situations Multi-Criteria Decision Making (MCDM) techniques have been developed. The aim of this article is to suggest a method to rank and hence choose a university for students’ admission using the method Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). To achieve the goal a novel distance measure has been proposed, and some axiomatic properties have also been proved for the same. The proposed approach aids in the process of university selection by ranking the universities based on certain criteria in fuzzy environment. The results obtained suggest that the proposed model provides a accurate way to select the best university among the large number of choices available for the considered universities. The paper settles with a discussion of a case study and experimental findings.

Suggested Citation

  • Mansi Bhatia & H. D. Arora & Riju Chaudhary & Vijay Kumar, 2024. "A Study on the Efficiency of Divergence Measure in Fuzzy TOPSIS Algorithm for Multi-attribute Decision Making—A Case Study on University Selection for Admission," Springer Series in Reliability Engineering,, Springer.
    • Handle: RePEc:spr:ssrchp:978-3-031-55048-5_18
    DOI: 10.1007/978-3-031-55048-5_18
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