Bipolar Intuitionistic Fuzzy Graph Centrality-Based Decision-Making Model to Prioritize Locations for Healthcare Camp during COVID-19
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Date
2025
Journal Title
Journal ISSN
Volume Title
Publisher
Elsevier
Abstract
Centrality measure is one of the important tools in graph theory to measure the significance of the vertices in the graph. When uncertainty exists in the vertices and their relations, the fuzzy graph helps to handle such scenarios. Bipolar intuitionistic fuzzy graph is an extension of fuzzy graph, effectively deal with uncertainty by assigning membership and nonmembership degrees in a bipolar perspective. In this chapter, the centrality measures such as degree, in-degree, and out-degree centrality measures in the bipolar intuitionistic fuzzy graph are defined. Additionally, a decision-making model is designed based on the degree centrality measure. Further, an illustration of this model is provided for prioritizing the locations to setup healthcare camp during COVID-19 pandemics. © 2025 Elsevier B.V., All rights reserved.
Description
Keywords
Applied Linguistics, Bipolar Intuitionistic Fuzzy Graph, Decision-Making, Degree Centrality, Infectious Disease, Knowledge Representation and Reasoning, Location Selection, Mathematical Optimization, Operations Research
Turkish CoHE Thesis Center URL
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N/A
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N/A
Source
Volume
Issue
Start Page
297
End Page
309
