COVID-19 pandemic poses unprecedented challenges to the world health system, prompting academics and health professionals to develop appropriate solutions. Researchers reported different COVID-19 vaccines introduced by institutions and companies around the globe, which are at different stages of development. However, research developing an integrated framework for selecting and ranking the optimal potential vaccine against COVID-19 is minimal. This paper aimed to fill this gap by using a hybrid methodology based on ELimination Et Choice Translating REality III (ELECTRE III)–Genetic Algorithm (GA) and Technique of Order Preference Similarity to the Ideal Solution (TOPSIS) approach to select the optimal SARS-CoV-2 vaccine. ELECTRE III method yields a fathomable analysis of the concordance index, while GA is known for its ability to disaggregate decision-making preferences from holistic decisions. TOPSIS is preferred for picking an ideal and an anti-ideal solution. Thus, combining ELECTRE III-GA and TOPSIS is considered the best model to assess vaccines against the pandemic. The results confirm that the best vaccines rely on a high level of safety, efficacy, and availability. Our developed evaluation framework can help healthcare professionals and researchers gain research information and make critical decisions regarding potential vaccines against the disease.

中文翻译：

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基于 ELECTRE III 遗传算法和 TOPSIS 方法的混合方法用于选择最佳 COVID-19 疫苗

COVID-19 大流行给世界卫生系统带来了前所未有的挑战，促使学者和卫生专业人员制定适当的解决方案。研究人员报告了全球机构和公司推出的不同 COVID-19 疫苗，这些疫苗处于不同的开发阶段。然而，开发用于选择和排列针对 COVID-19 的最佳潜在疫苗的综合框架的研究很少。本文旨在通过使用基于 ELimination Et Choice Translating REality III (ELECTRE III)-遗传算法 (GA) 和与理想解决方案相似性顺序偏好技术 (TOPSIS) 方法的混合方法来选择最佳 SARS- CoV-2 疫苗。ELECTRE III 方法可对一致性指数进行深入分析，而遗传算法以其将决策偏好与整体决策分开的能力而闻名。TOPSIS 是选择理想和反理想解决方案的首选。因此，将 ELECTRE III-GA 和 TOPSIS 结合起来被认为是评估针对大流行的疫苗的最佳模型。结果证实，最好的疫苗依赖于高水平的安全性、有效性和可用性。我们开发的评估框架可以帮助医疗保健专业人员和研究人员获得研究信息，并就潜在的针对该疾病的疫苗做出关键决策。结果证实，最好的疫苗依赖于高水平的安全性、有效性和可用性。我们开发的评估框架可以帮助医疗保健专业人员和研究人员获得研究信息，并就潜在的针对该疾病的疫苗做出关键决策。结果证实，最好的疫苗依赖于高水平的安全性、有效性和可用性。我们开发的评估框架可以帮助医疗保健专业人员和研究人员获得研究信息，并就潜在的针对该疾病的疫苗做出关键决策。