Modeling And Optimizing Methods Research In Job Shop Scheduling

With economic of market development, the characteristics of multi-species and small quantity has become the focal point of the market which manufactory racing to control.Therefore, manufacture enterprises should be asked to range sequences rationally, take advantage of resource efficiently, shorten time limit for a project and reduce the cost of producing. Effective Job-shop sehedule technology can boost the collocation of corporation resources.It also can improve productivity and reduce cost.This will enhance the capacity of the corporation.The job-shop scheduling research belongs to the combination optimization category, it is the typical NP(Non-deterministic Polynomial) difficult question,its research has great theory significance and practical significance.Therefore,it has become the production enterprises and general scholars'research hot spot.The genetic algorithm has the organization sense,auto-adapted and parallelism,it has own superiority while solving complex combination optimization questions,it is introduced in the job-shop scheduling questions'research.This paper introduces the shop scheduling problem under advanced manufacturing mode,studies the theory of job-shop scheduing problem. Genetic algorithm is effective to solving the job-shop scheduing problem,this paper analyses the development and basal theory of genetic algorithm,including concept and operational process,advances a new precocity standard and new choice method,test this improved genetic algorithm to the shop scheduling problem.Then,the paper do some research on the dynamic job shop scheduling and put forward the scheduling strategy combined with event-driven strategy and cycle strategy.The cycle strategy base on the rolling-window-technology.The systems design is done for the machine fault problem in dynamic job shop scheduling .Then use the genetic algorithm to solve this kind of dynamic problem and test it by FLEXSIM.