Research On Flexible Job Shop Scheduling Problem With Buffer Constraints

In the actual scheduling process of flexible job shop scheduling,the corresponding buffer capacity of equipment is limited,and the buffer capacity and buffer type configuration of each machine may be different,which will cause the jobs to be locked on the machines,and even the inapplicability of the job scheduling scheme.Therefore,when establishing the flexible job shop scheduling model,the impact of buffer constraints on the job scheduling scheme should be fully considered,that is the impact of buffer constraints should be considered when optimizing the job shop scheduling plan.In the context of flexible manufacturing workshop environment,the optimization of flexible job shop scheduling problem with buffer constraint according to the characteristics of the impact of single output buffer and input-output buffer is studied in this paper.And it is applying to the optimization process of actual job shop scheduling scheme,which effectively completes the optimization of flexible job shop scheduling problem with buffer constraint.The main research work carried out by this paper is as follows:(1)The model of flexible job shop scheduling problem with output buffer constraint is constructed.According to the characteristics of flexible job shop scheduling and the impact of machine’s output buffer capacity on job scheduling,the characteristics of the problem are analyzed in detail in this paper.The machine blocking and process conflict caused by insufficient buffer capacity are analyzed,and the mathematical model of FJSP with output buffer constraint with the objective of minimizing the maximum completion time is established.(2)The flexible job shop scheduling problem model with output buffer constraint is solved by an improved genetic algorithm proposed in this paper.The encoding method,decoding mode and reasonable process conflict adjustment method are designed according to the characteristics of the problem and algorithm characteristics.In order to solve the problems,that traditional genetic algorithm has some disadvantages when solving the proposed problem,such as low quality of initial population,weak search ability of genetic algorithm,the generation method of initial population and the genetic operator of the algorithm are improved.The effectiveness of the algorithm improvement mechanism was verified by the experimental examples constructed based on the standard case library,and the feasibility of the algorithm was verified by the experimental examples constructed under different output cache capacities.Finally,the superiority of the improved genetic algorithm was verified by comparing with other algorithms.(3)Modeling and solving flexible job shop scheduling problem with input and output buffer constraints.Based on the output buffer constraint of machine tool,the problem constraint is extended.Considering the influence of different buffer type combinations on job scheduling,the mathematical model of flexible job shop scheduling problem with input-output buffer constraint is established with the objective of minimizing the maximum completion time.After further improving the decoding method of the algorithm,the improved genetic algorithm is used to solve the problem Finally,the correctness of the established mathematical model and the effectiveness of the algorithm are verified by an experimental example based on the standard case library.The superiority of the improved genetic algorithm is verified by comparing with other algorithms.(4)Engineering application of flexible job shop scheduling with input and output buffer constraints.Through a project example of a computer numerical control workshop,the feasibility of the flexible job shop scheduling model with input and output buffer constraints is further verified,and the job shop scheduling problem of flexible manufacturing workshop with buffer constraints is effectively solved.