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Keywords = (p,q)-rung probabilistic hesitant orthopair fuzzy environment

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20 pages, 1703 KiB  
Article
Weight Optimization Decision Algorithm in (p,q)-Rung Probabilistic Hesitant Orthopair Fuzzy Environments
by Jinyan Bao and Xiangzhi Kong
Symmetry 2023, 15(11), 2043; https://doi.org/10.3390/sym15112043 - 10 Nov 2023
Viewed by 1813
Abstract
Aiming at the fuzzification of a decision environment and the challenge of determining the weights associated with the interaction among decision-makers, this study offers an original method for (p,q)-rung probabilistic hesitant orthopair fuzzy multi-objective group decision-making, which is founded [...] Read more.
Aiming at the fuzzification of a decision environment and the challenge of determining the weights associated with the interaction among decision-makers, this study offers an original method for (p,q)-rung probabilistic hesitant orthopair fuzzy multi-objective group decision-making, which is founded on the weight optimization principle. Firstly, the notion of a probabilistic hesitant fuzzy set is expanded to a (p,q)-rung. Secondly, the determination of subjective and objective weights is accomplished through the utilization of the Analytic Network Process (ANP) and the Entropy Method. According to the degree of deviation and dispersion of each weight, an optimal objective function is constructed, and the neural network is used to iteratively solve for the best scheme of the comprehensive weight. Subsequently, the Elimination Et Choice Translating Reality (ELECTRE) approach was refined and applied to decision-making in the (p,q)-rung probabilistic hesitant orthopair fuzzy environment. Finally, comparative analysis was used to demonstrate the new method’s effectiveness and superiority. Full article
(This article belongs to the Section Mathematics)
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