The Research Of Workshop Production Scheduling Based On The Improved Immune Algorithm

Manufacturing job-shop scheduling problem is based on the demand for rational allocation of manufacturing resources, so as to achieve the purpose of rational use of production resources to enhance the economic efficiency of enterprises. Therefore job-shop scheduling plays a very important role in the production and operation activities of enterprises. The flow-shop (Flow Shop) scheduling problem is a simplified model of real enterprise production line. It is widely used in discrete manufacturing and process manufacturing. Solving this kind of scheduling problems, can greatly enhance the production efficiency and the competitiveness of enterprises, therefore, the flow-shop scheduling is valuable.The solving process of traditional scheduling algorithm for the flow-shop scheduling problem is often ineffective, and mainly due to too many constraint conditions of the method itself. Aiming at the study of flow-shop scheduling model and the characteristic of scheduling problem in flow-shop scheduling, a popular artificial immune algorithm instead of traditional scheduling algorithm, has been adopted in this paper. The artificial immune algorithm proposed adaptive crossover and mutation operators, as well as a method of population partition, and made a large scale simulation solving experiment on flow-shop scheduling problem.The algorithm which is proposed in this paper made a simulation experiment on flow-shop scheduling model comparing with traditional genetic algorithm and normal immune algorithm. The results shows that, the proposed algorithm was more effective than traditional algorithm in solving performance, algorithm convergence and maturity.