Research & Reviews: Discrete Mathematical Structures
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A novel similarity measure for interval value picture fuzzy Environment and extended TOPSIS
Title Description
Volume : [268] | Issue : [398] | Received : [269] | Accepted : [270] | Published : [271] [if 405 not_equal=””]| DOI : [405][/if 405]
Keywords
Interval-valued picture fuzzy set, similarity measure, multi-criteria decision-making, linear programming, TOPSIS
Abstract
Correct decision-making is the most arduous task in our daily life. The decisions are hard to make in the multi-criteria decision-making (MCDM) problems due to ambiguous and unexpected information. In order to cope with such uncertainties in the data, a new decision-making approach has been developed using a newly defined similarity measure under the framework of interval-valued picture fuzzy set (IVPFS), as an extension of picture fuzzy sets (PFS). In real-life, due to insufficient data, improper knowledge or inexperience of the decision makers (DMs), the weights of attributes are either unknown or not satisfactory or partially known. To tackle such situation, the optimal weights of attributes are acquired using linear programming (LP) from the weight information that is partially known in this study. An algorithm for the TOPSIS method has been developed. Numerical examples have been executed to determine the feasibility and suitability of the suggested model. The comparison analysis shows that the suggest strategy is more effective than the prevailing methods.
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