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DECISION MAKING APPROACH FOR BEST MOBILE PHONE SERVICE PROVIDER SELECTION USING LAPLACIAN ENERGY AND COSINE SIMILARITY MEASURES OF HESITANCY FUZZY GRAPH.

Authors :
Nallapareddy, Rajagopal Reddy
Shaik, Sharief Basha
Source :
International Journal of Industrial Engineering. 2024, Vol. 31 Issue 3, p524-541. 18p.
Publication Year :
2024

Abstract

Telecommunication is one of the essential necessities of everyday life. In India, the telecommunications sector has seen a significant increase in the day-to-day. Telecommunications service companies hold data about their customers, and crisp graphs are used to depict these records. Examining and selecting the best mobile phone service providers (MPSPs) based on operational restrictions will help determine the best MPSPs. The analysis of MPSPs may be regarded as a difficult decisionmaking issue. The aim of this article is to provide an outline to examine the performance of MPSPs and the selection of the best MPSP for customers in India. The statistical data were obtained from the Telecom Regulatory Authority of India between April 2019 and March 2021. A novel approach for cosine similarity measures (CSM) among hesitancy fuzzy graphs (HFG) and estimating the certified repute scores of the experts by determining the ambiguous information of hesitancy fuzzy preference relations (HFPRs) and the regular cosine similarity grades from one separable HFPR to some others. And consider "objective" and "subjective" information given by experts. According to CSMs, we define the Laplacian energy of an HFG. This research provides a solution to a decision-making problem by applying the newly developed cosine similarity measure and the Laplacian energy of hesitancy fuzzy graphs. The ranking order of all alternatives and the best one is determined by calculating the cosine similarity between each alternative and the ideal alternative. Finally, an illustrated example is provided to show the applicability of the proposed approach to the decisionmaking problem as well as its effectiveness. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10724761
Volume :
31
Issue :
3
Database :
Academic Search Index
Journal :
International Journal of Industrial Engineering
Publication Type :
Academic Journal
Accession number :
178454911
Full Text :
https://doi.org/10.23055/ijietap.2024.31.3.8205