Flow Shop Production Scheduling Method Based On Genetic Algorithm And Its Practical Application

The resources constraints in the shop flow will hold back the accomplishment of production plans. In a sense, whether the enterprise can survive market competition is determined by whether it can meet customers' demands in time, which is further determined by how efficiently the limited resources are used. The assignment of the scheduling is to arrange the detailed process line, time, machine and operation according to produce goal and constraints. Therefore, a good scheduling method can optimize the manufacture system and enhance economy benefit. However, according to the resource and procedure restriction, the theory of calculate complexity shows that most scheduling problems are belong to nondeterministic polynomial hard problem, and the research of results involves space' combination problem. At the same time, there are various dynamic events which can't predict in practical. So workshop scheduling is very complexity. Recently there is still very difficult in finding a general effective scheduling method.In light of the method and development about workshop scheduling, the paper analyses detailedly about the problems of workshop scheduling. Firstly, the crossover operator and select operator are improved in order to overcome the drawback of the simple genetic algorithm which astringency is too premature. The ameliorative algorithm is also applied to an example in the workshop scheduling. Moreover, the characterization of the mixed workshop scheduling and the coding, solutions of the mixed genetic algorithm are also discussed in detail. As a result, the proposed method is applied for engine workshop scheduling in Geely group Inc.. The results highlight that the proposed algorithm can effectively reduce the waiting time of machine and enhance the efficiency of the manufacture.