Research On Optimization Of A Group Automated Warehouse Based On Improved Particle Swarm Optimization Algorithm

With the development of modern technology and global economic integration,the operating environment of manufacturing companies in China has undergone earth-shaking changes,and these changes make the manufacturing companies must improve service quality and reduce operating costs in order to be able to Better adapt to market competitiveness.Warehousing and logistics links are an important part of manufacturing companies.The emergence of automated three-dimensional warehouses has brought great convenience to warehousing and logistics links,and has also become an important logistics hub.In the course of logistics operation,the choice of location allocation and picking route is the key factor affecting the operation of the entire logistics.Therefore,it is of great significance to carry out the allocation of goods and choose a reasonable picking route scientifically and reasonably.A Group is a well-known manufacturing enterprise in China,and its automated three-dimensional warehouse bears the entire enterprise's warehouse sorting work.The Group is currently building a modern logistics center to meet the needs of the country and even the entire customer base.This article analyzes the problems existing in the automated warehouse of Group A.Based on the existing problems,it optimizes the location allocation model and the picking route model,and verifies the rationality and effectiveness of the optimization.On the basis of reading a large number of documents,this paper studies the problem of location allocation and picking route optimization in automated three-dimensional warehouses.The main tasks are as follows:First of all,this paper discusses the development process of automated warehouses,and analyzes the research status of the distribution of goods and picking route optimization by domestic and foreign scholars.In addition,the optimization algorithm is analyzed,which lays a theoretical foundation for the follow-up study of this paper.Secondly,this article uses the Flexsim simulation software to simulate and simulate the automated warehouse,and takes the warehouse operation of Group A as an example.Through the simulation analysis,the problems existing in the current process are discovered,which provided practical and feasible basis for the following optimization of location and picking and optimization.Thirdly,with the goal of optimizing product storage efficiency,shelf stability,and product-to-product correlation,and aiming at the existing problems of multi-objective particle swarm optimization,three aspects of optimization and improvement are carried out.And verified the effectiveness of the improved algorithm.Through the example simulation of Group A,the rationality of location allocation optimization was verified.Fourth,the process of selecting picking operations is essentially the shortest path problem in operations research.With the shortest picking path as the optimization goal,the model of the picking path was established.The problems in the standard particle swarm optimization algorithm were optimized in three aspects,and the effectiveness of the algorithm was verified.Through the example simulation of Group A,the rationality of the picking route optimization was verified.