Scheduling Method Of Hybrid Flow Shop Based On Theory Of Constraint

With the rapid development of market economy and increasingly diversified consumer demand,more and more enterprises change their production mode from high-volume, standardized production with inventory to more variety, small batch production according to orders. The conversion makes the management technologies, such as Manufacturing Resource Planning (MRPII) can not meet the needs of reasonable production. TOC is a management and control method to maximize the capacity of bottlenecks so that the system'output-sales ratio can be maximized. TOC utilizes the merits of push and pull production to improve the overall efficiency of the system. It is one of the most popular production and management techniques at present.As a typical NP-Hard scheduling problem, Hybrid Flow shop scheduling attracts extensive attention of researchers. Generally it is hard to exactly get an optimum solution. It is mainly solved by some modern optimization algorithms such as branch and bound, heuristic, local search and so on currently. In this thesis, the scheduling method of Hybrid Flow shop based on TOC is proposed. The method is composed of four modules: recognition of bottleneck workstation, bottleneck workstation scheduling, buffer control mechanism based on DBR and nonbottleneck workstation scheduling. First, the method identifies the bottleneck of the system. Then optimize the scheduling of bottleneck facilities with modified Genetic Algorithm combining heuristic algorithm. After that, it applies buffer mechanism to decide the releasing strategy of jobs. Finally, it arranges the remaining processes with priority scheduling rules.In order to validate the efficiency of the method, the simulation procedure is designed to evaluate the performances of this algorithm. And the experimental results indicate that the method based on TOC has superiority on solving the Hybrid Flow shop scheduling problem.