Adaptive Metaheuristic Methods Based on the Covid-19 Virus’ Behavior and Measures for Fight It

Abstract

The research proposes the numerical optimization methods are based on metaheuristic methods on the basis of COVID-19 virus' behavior and measures to fight it. The novelty of research is defined by the fact, that to increase the numerical optimization efficiency, the following issues were developed. The anti-coronavirus optimization, which uses the normalized distance between people in an explicit form and the dynamic Levy flight parameter to modify the vector of human health characteristics at the stage of social distancing was improved. A power-law parameter to calculate the dynamic number of the weakest people was proposed. A local search based on the number account of days in quarantine to modify the vector of human health characteristics at the quarantine stage, arithmetic crossover based on the number of days in isolation to modify the vector of human health characteristics at the isolation stage were developed. A coronavirus optimization algorithm that uses dynamic mutation probability to modify the virion vector and coronavirus herd immunity optimizer that uses dynamic mutation probability to modify an individual's characteristic vector were improved. The proposed methods improve the speed and accuracy of finding a solution. The created metaheuristic methods based on the behavior of the COVID-19 virus and measures to fight it can be used in general and special-purpose intelligent systems.