Empirical study on the effect of population size on Differential evolution Algorithm

In this paper, we investigate the effect of population size on the quality of solutions and the computational effort required by the Differential evolution (DE) Algorithm. A set of 5 problems chosen from the problem set of CEC 2005 Special Session on Real-Parameter Optimization are used to study the effect of population sizes on the performance of the DE. Results include the effects of various population sizes on the 10 and 30-dimensional versions of each problem for two different mutation strategies. Our study shows a significant influence of the population size on the performance of DE as well as interactions between mutation strategies, population size and dimensionality of the problems.