Dual Hesitant Bipolar Fuzzy Hamacher Prioritized Aggregation Operators in Multiple Attribute Decision Making

In this paper, we investigate the dual hesitant bipolar fuzzy multiple attribute decision making problems in which there exists a prioritization relationship over attributes. Then, motivated by the idea of Hamacher operations and prioritized aggregation operators, we have developed some Hamacher prioritized aggregation operators for aggregating dual hesitant bipolar fuzzy information: dual hesitant bipolar fuzzy Hamacher prioritized average operator, dual hesitant bipolar fuzzy Hamacher prioritized geometric operator, dual hesitant bipolar fuzzy Hamacher prioritized weighted average operator, dual hesitant bipolar fuzzy Hamacher prioritized weighted geometric operator. Then, we have utilized these operators to develop some approaches to solve the dual hesitant bipolar fuzzy multiple attribute decision making problems. Finally, a real-world example is then analyzed to illustrate the relevance and effectiveness of the proposed methodology.