Abstract
COVID-19 disease, which highly affected global life in 2020, led to a rapid scientific response. Versatile optimization methods found their application in scientific studies related to COVID-19 pandemic. Differential Evolution (DE) and Particle Swarm Optimization (PSO) are two metaheuristics that for over two decades have been widely researched and used in various fields of science. In this paper a survey of DE and PSO applications for problems related with COVID-19 pandemic that were rapidly published in 2020 is presented from two different points of view: 1. practitioners seeking the appropriate method to solve particular problem, 2. experts in metaheuristics that are interested in methodological details, inter comparisons between different methods, and the ways for improvement. The effectiveness and popularity of DE and PSO is analyzed in the context of other metaheuristics used against COVID-19. It is found that in COVID-19 related studies: 1. DE and PSO are most frequently used for calibration of epidemiological models and image-based classification of patients or symptoms, but applications are versatile, even interconnecting the pandemic and humanities; 2. reporting on DE or PSO methodological details is often scarce, and the choices made are not necessarily appropriate for the particular algorithm or problem; 3. mainly the basic variants of DE and PSO that were proposed in the late XX century are applied, and research performed in recent two decades is rather ignored; 4. the number of citations and the availability of codes in various programming languages seems to be the main factors for choosing metaheuristics that are finally used.
Highlights
During the year 2020 human activities around the globe have been highly affected by the pandemic of SARS-COV-2 virus and related COVID-19 disease
This paper presents a survey of applications of Differential Evolution (DE) and Particle Swarm Optimization (PSO) for solving optimization problems related to COVID-19 pandemic in research papers that appeared in 2020—the first year of the global SARS-COV-2 outbreak
This discrepancy between the classical approach, based on experiments performed in the late 1990’s, and observed performance on problems currently widely used in PSO literature may be the reason of so large differences in swarm sizes noted in COVID-19 related papers: some authors follow classical choices, some set higher values as they note that it improves the quality of solutions that are found
Summary
During the year 2020 human activities around the globe have been highly affected by the pandemic of SARS-COV-2 virus and related COVID-19 disease. This paper presents a survey of applications of DE and PSO for solving optimization problems related to COVID-19 pandemic in research papers that appeared (at least in preprint version) in 2020—the first year of the global SARS-COV-2 outbreak. The section focuses on the first goal of this paper, namely reviewing and summarizing the main applications of DE and PSO in studies aiming at different aspects of COVID19-related research. It is determined which metaheuristics are more frequently used, and an attempt to give a reason for their popularity is performed. The information on what is lacking, or unclear, is not less important for the discussion on DE/PSO applicability, as it shows what is considered to be of little interest in particular field of science, or which details seems to be too technical to practitioners (especially when in a hurry during the global pandemic), even if they are of uttermost importance to researchers working on EA or SI methods
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
