An Extended Multi-Attributive Border Approximation Area Comparison Method for Emergency Decision Making with Complex Linguistic Information

Hua Shi (), Lin Huang, Ke Li, Xiang-Hu Wang and Hu-Chen Liu
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Hua Shi: School of Materials, Shanghai Dianji University, Shanghai 201306, China
Lin Huang: School of Management, Shanghai University, Shanghai 200444, China
Ke Li: School of Economics and Management, Tongji University, Shanghai 200092, China
Xiang-Hu Wang: School of Materials, Shanghai Dianji University, Shanghai 201306, China
Hu-Chen Liu: School of Economics and Management, Tongji University, Shanghai 200092, China

Mathematics, 2022, vol. 10, issue 19, 1-16

Abstract: In recent years, different types of emergency events have taken place frequently around the world. Emergencies need to be addressed in the shortest possible time since inappropriate or delayed decisions may result in severe secondary disasters and economic losses. To make emergency decisions effectively within a limited time, a new emergency decision-making model is proposed in this study based on double hierarchy hesitant linguistic term sets (DHHLTSs) and the multi-attributive border approximation area comparison (MABAC) method. First, the performance assessment information on emergency solutions provided by domain experts is represented by the DHHLTSs, which are very useful for managing complex linguistic expressions in a prominent manner. Then, we make an extension of the MABAC method to determine the priority of alternative solutions and find out the optimal one for an emergency event. Furthermore, the criteria weights for emergency decision making are determined objectively with a maximum comprehensive method. Finally, a practical public health example is provided and a comparative analysis is performed to illustrate the applicability and advantages of the proposed emergency decision-making model.

Keywords: emergency decision making; double hierarchy hesitant fuzzy linguistic term set (DHHLTS); MABAC method; maximum comprehensive method (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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