Genetic algorithm-based topology optimization: Performance improvement through dynamic evolution of the population size

Topological optimization tool using genetic algorithm as optimization algorithm are known as very expensive in computation time. In this paper, we study an approach to improve performance of topological optimization tool by introducing a dynamic variation of the population size of children during the process of optimization. This method allows to improve performance of each generation by adapting the number of children created and by introducing a coefficient of reproduction for each individual inside the population of parents. Through this coefficient of reproduction, the number of children assigns to each parent is calculated. The number of evaluations at each generation changes and the tool can saves evaluations in order to increase the number of iterations.