Parallelization of Memetic Algorithms for the problem of scheduling in the production systems of HFS type

The metaheuristics are approximation methods which deal with difficult optimization problems. The Work that we present in this paper has primarily as an objective the adaptation and the implementation of two advanced metaheuristics which are the Memetic Algorithms (MA) applied in the production systems of Hybrid Flow Shop (HFS) type for the problem of scheduling. The hybrid genetic algorithms or memetic algorithms are advanced metaheuristics ones introduced by Moscato in 1989. We will propose an adaptation of two methods to the discrete case on the problems of scheduling with the production systems (HFS). We present then a comparison between the Memetic Algorithms (MA) and the Parallel Memetic Algorithms with Migration (PMA_MIG). Finally we give the results obtained by its algorithms applied to HFS (HFS4: FH3 (P4, P2, P3) || Cmax and HFS4: FH2 (P3, P2) || Cmax) for the two problems: scheduling and assignment.