Multiobjective Optimization with Genetic Algorithms for the Release of Wolbachia Mosquitoes Models

Vector control by releasing Wolbachia-infected mosquitoes is a promising strategy to reduce the transmission of diseases such as dengue. Wolbachia is a bacterium that reduces the ability of mosquitoes to transmit these viruses. In this work, the two-sex mathematical model is used to analyze release strategies for Wolbachia-infected mosquitoes, combining suppression and replacement, based on ordinary differential equations (ODEs) to simulate the population dynamics of Wolbachia-infected and uninfected mosquitoes, and a multi-objective optimization algorithm based on genetic algorithms is used. The objective is to find strategies that adjust the timing and duration of the release of infected male and female mosquitoes to maximize their effectiveness through genetic algorithms, with NSGA-II being the most robust algorithm by finding multiple alternatives that balance effectiveness and efficiency, this is crucial in multi-objective optimization problems as it allows decision makers to choose between different strategies according to their specific priorities and constraints.