Scheduling on many stations, with a variable number of machines on each station (Flexible Flowshop), looking to minimize multiple objectives as makespan and total flow time is not a new problem, but it is a low investigated area which has non-optimal solutions for all the cases. Our objective in the problem we’ve approached was to develop a meta-heuristic based on Strength Pareto Evolutionary Algorithm (SPEA) that give us solutions to the problem described before and be applied through an algorithm to see the sequence, the values of the objectives [Pareto optimal solutions (Cmax, Cprom)] for each station and verify the effectiveness. We are analyzing a making decision problem on the C C