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Group Decision-Making Framework with Bipolar Soft Expert Sets
Ghous Ali, Muhammad Akram, Sundas Shahzadi and Muhammad Zain Ul Abidin

Multiattribute group decision-making is a process of selecting an appropriate alternative from the available alternatives with the judgments of multiple experts about the alternatives regarding multiple parameters, emerging as a very useful technique in several decision-making theories to simulate group decision-making processes, but various existing theories are not commonly helpful in considering certain important features of practical decision processes. For instance, existing theories usually do not permit the decision-makers to consider bipolarity of parameters in a system. This study initiates the theory of a new hybrid model for group decision-making, namely, bipolar soft expert sets as a natural extension of two existing models (that is, soft expert sets and bipolar soft sets) because presented model is very suitable to describe the bipolarity of soft information with the opinions of more than one experts. Some fundamental properties of the developed hybrid model are discussed, namely, subset, complement, agree-BSES, disagree-BSES, union, intersection, AND operation and OR operation. Our proposed concepts are explained with illustrative examples. Further, to demonstrate the applicability of our initiated model, two applications of our proposed hybrid model are explored along with developed algorithms to tackle different group decision-making situations, that is, selection of a suitable automobile and an appropriate restaurant. Finally, a comparison analysis of the proposed model with existing models, including bipolar soft sets and soft experts sets is provided to show the supremacy of our initiated model.

Keywords: Soft set, bipolar soft expert set, weighted parameters, algorithm

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