Abstract
Hard sets and soft sets must be adopted for several unknown logistical problems. This paper seeks to solve the cluster-based decision-making dilemma effectively based on fumigated soft environments. First of all, we are introducing an adjustable approach to resolution of decisions focused on fuzzy soft solutions. Then, the information and the degree of divergence dependent on a-similarity are introduced to determine the weights of the experts. In addition, with uncertain expert weights, we can create an effective cluster-based decision-making strategy. Finally, sensitivity analysis and comparative analysis was conducted with other established approaches.
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