Application of genetic algorithm to optimize unrelated parallel machines of flexible job-shop scheduling problem

In a competitive manufacturing environment, to reduce production costs, and effective use of production capacity and balance of factory load, hybrid production system configuration plays a critical role. The unrelated parallel machines of flexible job shop are employed in the hybrid production system. This kind of problem can be classified as FJSP and have been proven to be NP-hard problem. To solve FJSP, in this paper we propose an improvement genetic algorithms to minimize the total order completion time. The proposed method separate the chromosome used in traditional job shop scheduling problem into two parts, called operation assign (OA) and machine selection (MS). To deal with this chromosome, an improved genetic operation is utilized. Finally, in order to verify the feasibility of proposed method, the well-known examples Brandimarte´s MK1 to MK10 were used to prove the effectiveness of the proposed method.