The Study Of Distributed Scheduling Method

As advanced manufacturing mode for the 21th business enterprise,dispersed network manufacturing synthesizes many advanced philosophies of manufacturing pattern such as JIT,parallel engineering project,excellent manufacturing and so on.Its purpose is making out customer satisfied products with the most low cost.In this mode,how to carry out the organization,management and scheduling has became a new topic to be settled urgently. Shop production scheduling is one of key parts of production scheduling is one key parts of production management and control.The assignment of a schedule is that according to produce goal and restriction to arrange the detailed process line,time,machine and operation etc.Therefore,good schedule methods can enhance manufacture system's optimization character and economy benefit.In this thesis,a distributed manufacturing dynamic shop scheduling problem is researched under the dispersed network manufacturing mode.A modified GA is presented, which is capable of solving traditional scheduling problems as well as distributed scheduling problems.And a genetic algorithm with dominant genes is proposed to deal with distributed scheduling problems,especially in a flexible manufacturing system(FMS) environment.The main achievements of the paper are as follows.Firstly,the characteristics and the demands of the newly emerged dispersed network manufacturing are discussed,and then the shortages of previously used GAs in manufacturing scheduling are pointed out.Secondly,the keys and difficult points of GAs in job-shop scheduling are analyzed and details about the genetic operators designing,the colony initialization and other related factors are discussed.Thirdly,a modified GA is presented,which is capable of solving traditional scheduling problems as well as distributed scheduling problems.Various scheduling objectives can be achieved including minimizing makespan,cost and weighted multiple criteria.The proposed algorithm has been evaluated with satisfactory results through several classical scheduling benchmarks.Furthermore,the capability of the modified GA was also tested for handling the distributed scheduling problems. Finally,a genetic algorithm with dominant genes is proposed to deal with distributed scheduling problems,especially in a flexible manufacturing system(FMS) environment. The idea of dominant genes is to identify and record the critical genes in the chromosome and to enhance the performance of genetic research.To testify and benchmark the optimization reliability,the proposed algorithm has been compared with other approaches on several distributed scheduling problems.These comparisons demonstrate the importance of distributed scheduling and indicate the optimization reliability of the proposed algorithm.