A Group Emergency Decision-Making Method for Epidemic Prevention and Control Based on Probabilistic Hesitant Fuzzy Prospect Set Considering Quality of Information

Abstract Epidemics can bring huge impacts to economic operation and human health, a practical effective emergency decision-making (EDM) method is of great significance reduce all kinds losses slow the spread epidemics. In process EDM, decision information usually uncertain vague, psychological behaviors various perspectives makers (DMs) should be considered. Hence, this paper develops group (GEDM) under risk based on probabilistic hesitant fuzzy set (PHFS) cumulative prospect theory (CPT), in which (PHFPS) that combines PHFS CPT developed portray vagueness psychologies DMs. Moreover, experts’ creditability evaluation criteria generally different because differences their own knowledge structures, experience, individual preference so on. A formula proposed measure quality provided by experts for revising expert weights. addition, supporting GEDM epidemics are given. Finally, demonstrated an empirical case study COVID-19, comparison analysis rank-biased overlap model sensitivity conducted illustrate validity method.