This paper deals with an hybridation of two non-conventional optimization methods, genetic algorithms and a new based particle swarm, is proposed for optimization of multiobjective flow-shop scheduling problem in pharmaceutical industries. The comparison of results obtained by this hybridation and those obtained by the separate use of each one of the two methods shows the efficiency of the proposed approach.