Application Research Of Cross-cycle Batch Scheduling In A Large Connector Manufacturer

China's industrial economic system is gradually formed in its own development and in the process of undertaking industrial transfer in the developed countries.The production and manufacturing link is the core of China's industrial economy.And how to reduce the production cost and enhance the competitiveness of enterprises in the industry is the focus of attention of many enterprises.At present,China's manufacturing enterprises usually use artificial experience or enterprise resource planning method to plan production.However,this method can only make rough production plans rather than detailed production plans,and can not maximize the allocation of limited resources in the increasingly fierce market environment,resulting in the waste of resources and the increase of cost.Therefore,this paper,taking the actual enterprise production as an example,discusses the advantages and disadvantages of each solution,formulating the detailed production plan,and further discussing the solution method,providing the basis for the production plan of the manufacturing enterpriseIn this study,we focus on the capacitated lot-sizing problem with single-level,carry-over setups,and parallel machines and formulate this problem into a mixed integer programming model.In addition,a simulated annealing algorithm is developed to solve this problem.In this study,the main content of this method can be divided into two parts.In the first part,the method proposed in this paper is studied in a large connector factory.The results show that the profit produced by the detailed production plan made by this method in the different production environment is better than the actual production data of the enterprise and improve the original production plan of the enterprise.In the second part,the method of this paper is further studied.The results show that this method can solve the large-size capacitated lot-sizing problems with carry-over setups and provide production planning decision basis for more complex manufacturing environments.In the further studies,multiple-level capacitated lot-sizing problem and other algorithms may also be two good research directions.