Application of Interval Valued Intuitionistic Fuzzy Uncertain MCDM Methodology for Ph.D Supervisor Selection Problem

The selection of Ph.D (Doctor of Philosophy) supervisor is always a vital and interesting problem in academia and especially for students who want to carry out Ph.D. Nowadays, selecting a supervisor for Ph.D in a scientific manner becomes a challenge for any student because of the variety of options...

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Bibliographic Details
Published in:Results in control and optimization Vol. 15; p. 100411
Main Authors: Mandal, Shubhendu, Gazi, Kamal Hossain, Salahshour, Soheil, Mondal, Sankar Prasad, Bhattacharya, Paritosh, Saha, Apu Kumar
Format: Journal Article
Language:English
Published: Elsevier B.V 01.06.2024
Elsevier
Subjects:
AHP
Interval valued intuitionistic fuzzy number
PhD supervisor selection
Research institute
TOPSIS
PhD supervisor selection
Interval valued intuitionistic fuzzy number
AHP
Research institute
TOPSIS
ISSN:2666-7207, 2666-7207
Online Access:Get full text
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Summary:The selection of Ph.D (Doctor of Philosophy) supervisor is always a vital and interesting problem in academia and especially for students who want to carry out Ph.D. Nowadays, selecting a supervisor for Ph.D in a scientific manner becomes a challenge for any student because of the variety of options available to the scholar. In this context, the present study aims to formulate a model for Ph.D. supervisor selection from the offered alternatives in an academic institute. A hybrid multi-criteria decision making (MCDM) framework has been applied to select the suitable supervisor of the student’s preferred criteria under interval-valued intuitionistic fuzzy (IVIF) scenario. The IVIF Analytic Hierarchy Process (AHP) has been employed to prioritize the criteria, whereas IVIF Technique for order preference by similarity to ideal solution (TOPSIS) technique is engaged to rank the available supervisors based on criteria weight. A set of eight criteria and five alternatives have been considered for modeling the problem. Moreover, the potential criteria are weighted and ranked by the multiple decision makers in the present study. To examine the consistency and robustness of the proposed integrated approach, sensitivity analysis and comparative analysis have been carried out. From all the analyses, it can be conferred that the suggested approach is quite useful to apply in different decision-making scenarios.
ISSN:2666-7207
2666-7207
DOI:10.1016/j.rico.2024.100411