Research On Optimization And Implementation Technology Of Advanced Scheduling Algorithm For Garment Factory

Since this century,the development of information technology has made the information transmission of the clothing industry more and more convenient.Personalized customization has gradually become the customer demand.The traditional clothing manufacturing industry is no longer facing single style and large batch orders,but multi style,personalized and small batch orders.The mass production management system is no longer suitable for the discrete clothing processing and manufacturing industry at this stage,How to make production plan accurately and quickly in the face of a variety of rapidly changing orders and ensure as much as possible to improve the delivery rate of orders has become an important symbol of the competitiveness of a garment factory.In view of this trend of discrete manufacturing,this paper uses genetic algorithm as the core to design and implement an APS(Advanced Planning and scheduling)system for garment factories,which can help enterprises make production plans quickly and accurately in the face of discrete orders,and improve the competitive-ness of enterprises.The first chapter summarizes the purpose and significance of this design,summarizes the research status at home and abroad from the development process of advanced planning and scheduling system,and deeply analyzes the application of scheduling system in domestic garment factories.In the second chapter,the core of scheduling system-job shop scheduling and flexible job shop scheduling problem have been deeply studied.After the introduction of various algorithms for solving the scheduling problem,the genetic algorithm is selected as the algorithm in this design.In the third chapter,based on genetic algorithm,the solution process of flexible job shop scheduling problem have been described.In addition,an improved genetic algorithm is proposed for garment factories,and three fitness evaluation systems are proposed based on the actual process.At the same time,the selection method of elite retention and hierarchical crossover,combined with the close relatives deletion method,can improve the convergence precision of the algorithm under the condition of appropriately slowing down the convergence rate of the algorithm.a flexible job shop scheduling example proposed by Brandimarte is used to optimize the parameters of the algorithm,and a comparative experiment is carried out to prove the superiority of the improved algorithm.The fourth chapter describes the advantages of using B/S architecture,and using Java,springboot,mysql,Java Script,Vue and other open source frameworks or technologies to design and implement the advanced planning and scheduling system for garment factories.The fifth chapter detailly explains the process of scheduling.The user inputs the order task information and production line employee's capacity into the database.Then,user selects the order production line and tries to create a scheduling record.After receiving the request,the server executes the genetic algorithm to find the optimal solution,and finally displays the scheduling result in the form of Gantt chart.The sixth chapter summarizes the whole paper and puts forward the follow-up improvement scheme.It is hoped that the research in this paper will play a positive role in guiding the further digital development of China's clothing industry,and has reference significance for the design of advanced planning and scheduling system in the clothing industry.