I am using a cooperative coevolutionary genetic algorithm, the algorithm is given in A cooperative coevolutionary approach to function optimization by DeJong et. al. (1994), for optimizing a 62 dimensional function. One difference being that I am minimizing instead of maximizing. I am also using roulette selection, however since I need to minimize, the fitness is defined as the (maximum_fitness - actual_function_value).
I tried running the algorithm with 10, 20, 50 and 100 individuals, each about 5 runs. The one with 20 individuals had the lowest value of convergence while the others converged at what seems to be a higher local minima.
As far as I know, the more the individuals, the higher is the chance of escaping local minima. Is there any reason why that is not true for my case?