Genetic operators for the multiobjective flowshop problem

One of the must important issues in Genetic Algorithms is the right selection of crossover and mutation operators. Genetic Operators are even more important for non binary chromosomes due to their high impact on the results. This work presents a comparative analysis of different crossover and mutation operators applied to a genetic algorithm for the multJobjective flowshop problem. The algorithm used is adapted from the partition method proposed by Tagami et al. and builds a Pareto's frontier. We minimize the makespan and the mean flowtime.