Hybrid TODIM Method with Crisp Number and Probability Linguistic Term Set for Urban Epidemic Situation Evaluation

Abstract

Emergency medical services during the COVID-19 epidemic have become the focus of worldwide attention, and how to effectively respond to urban epidemic situation during a complex environment has become a global challenge. Emergency decision-making can be considered as a multicriteria decision-making (MCDM) problem, which involves multiple criteria or attributes about qualitative and quantitative aspects. So, in this paper, based on the TODIM method, a hybrid TODIM method with crisp number and probability linguistic term set is first provided to evaluate the severity of urban COVID-19 epidemic situation during a complex humanitarian crisis environment. In this hybrid method, the quantitative aspects are evaluated on the basis of precise numerical values, and the qualitative aspects are evaluated by means of probability linguistic term set, which can not only express their judgments or linguistic preference with multiple linguistic terms but also reflect different importance degrees or probability degrees of all the possible linguistic information or preference information. In addition, the concept of entropy and probability linguistic entropy is applied to induce hybrid criteria weight information. Furthermore, sensitivity analysis of the parameter about attenuation factor of the losses in the hybrid TODIM method, which considers the psychology factors and cognitive behavior of the DMs, is further conducted on a case study, to verify the effectiveness and stability of the proposed method for urban epidemic situation evaluation according to the results of this study.

Rise of multiattribute decision‐making in combating COVID‐19: A systematic review of the state‐of‐the‐art literature

“…Once again, MADM is pioneered in scenarios regarding infected patients and bed capacity to provide support for effective public health policies for national, regional and local intervention. In the following study, 56 the authors asserted that their ultimate and harmonic integration is needed considering the importance of emergency medical services during the COVID‐19 pandemic. They highlighted that the response to the pandemic affects the rate of mitigating its problems.…”

“…Notably, the evaluation and/or validation in MADM coincides with the principle of testing the reliability and stability of the decision results. 56 Six common approaches are presented to evaluate and/or validate the MADM results in the related literature as follows: Comparative analysis: One of the most common approaches to verify the strength, steadiness and validity of a proposed model, method or technique in MADM is comparative analysis. In this approach, the superiority of the proposed decision support approach is tested compared with the existing one.…”

“…This sensitivity can indicate and evaluate the validity and stability of the ranking results in the proposed methodology compared with other MADM methodologies by competitors. 56 …”

“…Figure 6 shows the 16 countries in which the studies included in this review were conducted. The selected articles' geographical distribution in terms of numbers and percentages shows that the most prolific contributors were from India 59 , 63 , 65 , 73 , 75 , 76 , 79 , 80 , 82 , 83 , 88 , 93 with 12 studies; China 56 , 58 , 72 , 74 , 86 , 90 , 96 with seven studies; Turkey, 51 , 60 , 71 , 91 , 92 Pakistan, 54 , 57 , 67 , 78 , 85 and Malaysia 10 , 37 , 52 , 68 , 89 with five studies each; Saudi Arabia 69 , 77 , 94 with three studies; Iraq, 61 , 66 Egypt, 44 , 62 Iran, 50 , 81 and Italy 70 , 87 with two studies each; and Serbia, 49 Philippines, 53 Brazil, 55 ...…”

A Revised Grey Relational Analysis Method for Multicriteria Group Decision-Making with Expected Utility Theory for Oil Spill Emergency Management

“…In general, multiple-criteria problems can be divided into two categories: multiple-criteria discrete alternative problems and multiple-criteria optimization problems [37]. Many methods and techniques have been developed to solve these two categories of problems [15,[38][39][40], such as data envelopment analysis (DEA) [41], the analytic hierarchy process (AHP) [42], grey relational analysis (GRA) [43], the compromise ranking method (called VIKOR) [31], the technique for ordering preference by similarity to ideal solution (TOPSIS) [44], the decision-making trial and evaluation laboratory (DEMATEL) [45], the preference ranking organization method for enrichment of evaluations (PROMETHEE) [46], multiattribute utility theory (MAUT) [47], and evolutionary multiobjective optimization [48].…”