This paper addresses a problem of machining determination of input quantity in a multi-stage flexible flow system with non-identical parallel machines considers a subcontracting, machining restraint, and machine yield. We develop a nonlinear programing with the objective of minimizing the sum of in-house processing cost and subcontracting cost. To solve this model, we introduce a single-processor parallel genetic algorithm(SPGA) to improve a weak point for the declined robustness of simple algorithm(SGA). The efficiency of the SPGA is examined in comparison with the SGA for the same problem. In of examination the SPGA is to provide the excellent solution than the solution of the SGA.