A heterogeneous multi-attribute case retrieval method based on neutrosophic sets and TODIM for emergency situations

Abstract

Heterogeneous multi-attribute case retrieval is a crucial step in generating emergency alternatives during the course of emergency decision making (EDM) by referring to historical cases. This paper develops a heterogeneous multi-attribute case retrieval method for EDM that considers five attribute formats: crisp numbers, interval numbers, intuitionistic fuzzy numbers, single-valued neutrosophic numbers (SvNNs), and interval-valued neutrosophic numbers (IvNNs). First, we propose a similarity measurement of IvNNs and calculate the attribute similarities for the five attribute formats. The attribute weights are established using an optimal model. Next, the case similarities are calculated and the set of the similar historical cases is constructed. Furthermore, the evaluated information based on heterogeneous multi-attribute from similar historical cases is provided, and the calculation method for the evaluation of utility based on TODIM (an acronym for interactive and multi-criteria decision-making in Portugese) is proposed. The most suitable historical case is determined based on the case similarity and the evaluated utility. From this, the emergency alternative is generated. Finally, we demonstrate the efficacy of the proposed method with a case study and conduct comparisons against the performance of existing methods to assess the validity and superiority of the proposed method.

A New Multi-Attribute Decision Making Method for Overvalued Star Ratings Adjustment and Its Application in New Energy Vehicle Selection

“…There are abundant decision making methods in the field of multi-attribute decision making, such as TOPSIS [36], TODIM [37], VIKOR [38], ELECTRE [39], MULTIMOORA [40], and so on. Multi-attribute decision making methods were extended to various fields, including distribution center site selection [41], the selection of emergency solutions [42], the selection of disaster handling solutions [43], and so on. Wang et al used the fuzzy AHP method and fuzzy deviation maximizing method to calculate attribute weights and combined five types of multi-attribute decision methods, namely the TOPSIS, TODIM, VIKOR, PROMETHEE, and ELECTRE methods, with the simple dominance principle to rank the bidding options and select the best one [44].…”

A Dynamic Emergency Plan Generation Method Considering Different Situations and Limited Resources

“…Zheng [16] proposed dynamic case-based reasoning group decision-making for emergency plan generation, with the ability to adjust the generated emergency plans based on changing emergency situations. Zhang [17] developed a heterogeneous multi-attribute case retrieval method for emergency plan generation considering five information types: crisp numbers, interval numbers, intuitionistic fuzzy numbers, single-valued neutrosophic numbers, and interval-valued neutrosophic numbers. Yu et al [27] proposed a new case adaptation algorithm to accelerate the adaptation process, which was able to generate emergency plans more efficiently.…”

“…When handling emergency situations, emergency plans are the key measures and elements, and have direct influence on whether emergency situations are successfully handled or not. Therefore, due to the importance and influence of emergency plans, studies related to emergency planning have been conducted from various perspectives, such as evaluation of emergency plans [8][9][10], mathematical programmingbased emergency plan formalization [11][12][13], case-based reasoning emergency plan generation [14][15][16][17], hierarchical task network-based emergency plan generation [18,19], and various features (uncertainty, incomplete information, etc.) involving consideration of EEs within emergency plan generation [18][19][20][21].…”