Prospect Score Function-Based TODIM with Probabilistic Hesitant Fuzzy Sets: A Risk-Psychology-Embedded Decision Framework for Emergency Alternative Selection

Extreme weather-induced flooding poses significant threats to urban safety and public health. The complexity of emergency alternative selection faced by disaster management authorities intensifies crisis resolution challenges. Optimal resource allocation and prioritized response strategies constitute core components of disaster management, where flood emergency alternative evaluation emerges as a quintessential Multi-Attribute Group Decision-Making (MAGDM) problem, directly impacting the timeliness and effectiveness of emergency response efforts. In this paper, a novel probabilistic hesitant fuzzy TODIM (an acronym in Portuguese for Interactive Multi-Attribute Decision-Making) method is proposed to optimize emergency response. To address the absolutization present in existing studies, a new score function grounded in prospect theory is devised to solve probabilistic hesitant fuzzy sets (PHFSs) by interpreting the probabilistic characteristics. Subsequently, by combining with the maximum deviation method, an attribute weight determination model is introduced. Besides, probabilistic hesitant fuzzy Wasserstein similarity measure is constructed and an expert weight determination approach is designed on this basis. Furthermore, the specific steps of the novel TODIM method are introduced. As a critical component of the TODIM method, the loss aversion coefficient is derived through a grey relational analysis-based approach, aiming to reflect risk psychology of decision-makers (DMs) through the correlation of evaluation information. By applying the method to emergency alternative selection for the urban flood disaster in Zhengzhou, its feasibility is demonstrated. Simulation analysis and comparison analysis with existing methods demonstrate the feasibility and practicality of the proposed method.