Abstract
In emergency decision making (EDM), it is necessary to generate an effective alternative quickly. Case-based reasoning (CBR) has been applied to EDM; however, choosing the most suitable case from a set of similar cases after case retrieval remains challenging. This study proposes a dynamic method based on case retrieval and group decision making (GDM), called dynamic case-based reasoning group decision making (CBRGDM), for emergency alternative generation. In the proposed method, first, similar historical cases are identified through case similarity measurement. Then, evaluation information provided by group decision makers for similar cases is aggregated based on regret theory, and comprehensive perceived utilities for the similar cases are obtained. Finally, the most suitable historical case is obtained from the case similarities and the comprehensive perceived utilities for similar historical cases. The method is then applied to an example of a gas explosion in a coal company in China. The results show that the proposed method is feasible and effective in EDM. The advantages of the proposed method are verified based on comparisons with existing methods. In particular, dynamic CBRGDM can adjust the emergency alternative according to changing emergencies. The results of application of dynamic CBRGDM to a gas explosion and comparison with existing methods verify its feasibility and practicability.
Highlights
In recent years, several major emergency events have occurred, including the Indian Ocean Tsunami in 2004, the 12 May Wenchuan Earthquake in China in 2008, the missing Malaysian Airlines MH370 in 2014, and the fire in Rio de Janeiro, Brazil, in 2018
This study proposes a dynamic method based on case retrieval and group decision making (GDM), called dynamic casebased reasoning group decision making (CBRGDM), for emergency alternative generation
To verify the effectiveness and practicability of the proposed CBRGDM approach, we compare it with four existing emergency decision making (EDM) methods, including the EDM based on the Case-based reasoning (CBR) method (Fan et al 2014), called CBR-F; the method based on the CBR and interval-valued Pythagorean fuzzy linguistic weighted averaging (IVPFLWA) operator (Du et al 2017), called CBR-IVPFLWA; the GDM method based on the prospect theory (Wang et al 2015), called CBR-GDMPT; and the GDM method based on Intervalvalued Pythagorean fuzzy linguistic variable (IVPFLV) and prospect theory (Ding et al 2019), called CBRIVPFLVPT
Summary
Several major emergency events have occurred, including the Indian Ocean Tsunami in 2004, the 12 May Wenchuan Earthquake in China in 2008, the missing Malaysian Airlines MH370 in 2014, and the fire in Rio de Janeiro, Brazil, in 2018. There are certain limitations for instance, the aspiration levels of the attributes are required, which is difficult because they must be determined in advance To avoid this problem, the regret theory has been used to express the psychological behavior of decision makers. It is necessary to consider the dynamic evolution of emergencies in EDM Against this background, considering the advantages of CBR and GDM, a dynamic method based on case retrieval and GDM, called dynamic case-based reasoning group decision making (CBRGDM), is proposed to generate a suitable alternative in EDM. We use an improved GDM method to select the most feasible historical case, in which we apply IVPFLVs to represent fuzzy information and regret theory to express the decision makers’ psychological behavior. Once the similarity threshold is determined, the similar case set can be obtained
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