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Selection of cloud service providers using MCDM methodology under intuitionistic fuzzy uncertainty

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Abstract

Cloud computing concept has taken prodigious growth over the last decade. With the vast options of Cloud Service Providers available nowadays and a variety of services and facilities to choose from, it is of paramount necessity to opt for the best cloud service provider based on multiple criteria and requirements ascertained by any organization or an individual. This study selects the cloud service provider based on various conflicting criteria. In this paper, pentagonal intuitionistic fuzzy number (PIFN) with MCDM tool analytic hierarchy process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods have been used to rank the Cloud Service Providers (CSPs). Firstly, the criteria PIFN weights are calculated using comparison matrices with the help of decision-makers (DMs), and then, FTOPSIS is done to obtain the final ranking. Sensitivity and comparative analyses have been conducted to see the changes in ranking obtained. These analyses help analyze the most sensitive criteria and thus help the researchers mark and evaluate for future scope and further research.

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Ghorui, N., Mondal, S.P., Chatterjee, B. et al. Selection of cloud service providers using MCDM methodology under intuitionistic fuzzy uncertainty. Soft Comput 27, 2403–2423 (2023). https://doi.org/10.1007/s00500-022-07772-8

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