Search And Implementation Of Advanced Planning And Scheduling System Based On Consumption Loop Control And Genetic Algorithm

Advanced planning and scheduling system is a system used to schedule production requirements in the manufacturing industry.A good scheduling system can help enterprises and factories to efficiently complete orders,improve machine efficiency and reduce losses in the production process.For advanced planning and scheduling system,the core is how to solve the flexible shop-shop scheduling problem.At present,there are many researches on this aspect,which provide their own solutions to this problem from different dimensions.However,most of the solutions proposed in these studies are still in the laboratory stage,and there are generally three problems :(1)the scenarios considered by the algorithms are too simple to adapt to the complex situations in actual production.(2)Most algorithms only take a single goal as the final solution standard,which is not suitable for the various requirements of scheduling results in actual production.(3)When the scale of production demand expands,the difficulty of algorithm encoding and decoding increases greatly.And it is difficult to guarantee the initial population qualityAiming at the above three problems,this thesis makes an in-depth analysis of the flexible shop scheduling problem,and implements a new advanced scheduling and scheduling system based on the actual production situation.The main features of the system are as follows:(a)Based on Kanban theory,this thesis proposes a consumption loop control model that can deal with real complex business scenarios.The model proposed in this thesis can comprehensively consider the real complex factors,such as machine,store,carrier,product information,process and factory,and model these complex factors based on Kanban theory.(b)Based on the consumption loop control model,a multi-objective genetic algorithm is designed and implemented,which can be decoupled from the production scale and has high quality initial population.On the one hand,the genetic algorithm proposed in this thesis can evaluate the performance of individual goals with the help of the consumption loop control model,and deal with the scheduling needs of multiple goals by setting the weight of goals.On the other hand,the proposed algorithm designs a high-level encoding and decoding approach that successfully decouples the quantity of production requirements and ensures the quality of the initial population.(c)This thesis designs and implements a high-level planning and scheduling system,which is capable of handling real and complex business scenarios,meeting multi-objective scheduling requirements,and solving long-term mass production requirements.The system uses the model to deal with real business scenarios,uses the evaluation ability of the model to meet the multi-objective scheduling needs,and uses the genetic algorithm decoupled from the production scale to solve the long-term mass production needs.