Job Shop Scheduling Problem With Multiple Process Routes And Lot Split Based On Improved Genetic Algorithm

Job shop scheduling problem is a key line in production management, which plays an important role in improving production efficiency and production benefit. Job shop scheduling problem is a typical NP hard problem with multiplicity, complexity and uncertainty. Under today’s highly competitive market environment diversified and personalized has become the main demand of customers, so the single variety of production mode is difficult to obtain the high efficiency. At present multi process and batch production job shop scheduling problem has received widespread attention. In this paper, the improved genetic algorithm is designed according to the characteristics of the multi process and the batch production job shop scheduling problem. The main research content of this paper is as follows:In the actual production process, there are various processing of various parts of the route, and the total number of each step of the work piece processing route included undetermined. In this paper, the optimization goal is minimum makespan, and the work piece machining process route and priority synchronization optimization model has been established. For simultaneous optimization problem, we design process based on the priority of matrix coding, matrix processing line first as the work piece, the remaining steps of each process as each work piece priority. Meanwhile, in order to avoid infeasible solution, optimized to improve performance of the algorithm, design a variety of crossover and mutation methods of operation and problems with adaptation. By way of example simulation show that the algorithm can effectively solve the multi-craft job shop scheduling problem.Aiming at the problem of job shop scheduling in batch production, this paper considers the impact of the transport time on the whole processing time, and establishes a mathematical model based on the minimum completion time. In the process of batch production scheduling problem, the change of the number of batches will lead to the change of chromosome length. The design of this problem is based on the same process, which can effectively avoid the generation of infeasible solutions and improve the operating efficiency of the algorithm. How to batch production process is the key to solve the problem. In view of the problem, this paper analyzes the advantages and disadvantages of two kinds of batch method in comparison with the early fixed batch and random batch.On the basis of the above theoretical research, using VC++ to prepare the corresponding optimization design program, the optimization results show that the improved genetic algorithm is effective.