关键链约束理论解决柔性车间调度问题

Critical Chain Theory of Constrain for the Flexible Job Shop Scheduling Problem

柔性作业车间的调度难题一直以来都是NP难题,随着加工零件数量和机床数量的增加,调度优化难度将会以呈指数倍增长。本研究提出以约束理论为基础依托,选用最小临界比规则及遗传算法,结合各自的优点对柔性作业车间基于关键链进行调度优化,有效的解决了传统遗传算法容易陷入局部最优和最小临界比规则鲁棒性不强等问题。使设计的调度算法更加地符合车间真实的制造生产状况,改善了制造过程中资源设备利用率相对较低的问题,把设计的算法和传统遗传调度算法解决典型的柔性作业车间难题得到的结论相对比,验证设计算法的优势。

Flexible job shop scheduling problem has always been a NP hard problem, With the increase of the number of the job and machine. The difficulty times of scheduling optimization will be increasing exponentially. This study puts forward on the basis of theory of constraints, and selects the minimum critical ratio rules and genetic algorithm, Combining the respective advantages and based on critical chains for the flexible job shop scheduling optimization, effectively solve the traditional genetic algorithm easy to fall into local optimum and minimum critical ratio’s robustness is not strong. Make the algorithm of design is more joint workshop actual production conditions. To enhancing the resource utilization of manufacturing process. The design algorithm and traditional genetic algorithm to solving a typical flexible job shop problem is compared and verified the advantages of the design of algorithms.