The Research And Application Of Location Decision Optimization For Typical Warehouseing Operations

In recent years,with the rapid development of e-commerce,the logistics industry has gradually become one of the mainstream industries to drive the growth of the national economy and occupies an important position in the current social development.As an important part in logistics process,storage operation is responsible for the temporary storage of product production and circulation,its cost highest.Therefore,the optimization of the location decision has great theoretical significance and engineering application value,not only guarantee the stable operation,but also benefit the optimization of the storage resources and the core competitiveness of enterprises enhanced.However,according to the analysis of the development status of logistics industry in China,there are some shortcomings in the application of application of location decision optimization.Under the new trend of intelligent development of logistics industry,the optimization of intelligent decision-making for warehousing operation has been widely concerned by scholars and industry circles.Based on the needs of the development of modern logistics management,this paper use data mining technology and intelligent optimization algorithm to carry out a related research on the location decision optimization in the typical warehouse operation process.The main research work is as follows:(1)Analysis and design of location decision system for typical warehousing operationOn account of the system requirements analysis,a warehouse operation decision system architecture based on Service-Oriented Architecture(SOA)is proposed.The optimization method of intelligent location decision is designed to be a relatively independent and reusable distributed service,which satisfies the reconfigurable requirement of the system and promotes the extensibility and maintainability.Based on the service oriented system architecture,the system structure with the function of optimization storage is given;Based on the entity relationship analysis(E-R),the system database is designed to provide data storage for decision-making optimization.(2)Inventory operations location decision optimization method based on spectral clustering is proposedIn modern logistics system the quantity of orders and materials is more and more large,there are statistical characteristics of demand association between materials.By making full use of these related information can optimize the layout of storage and improve the efficiency.It takes the parallel sorting as the research object to excavate the data of historical orders,models of the material similarity measurement,material aggregation optimization and inventory operations location decision optimization aiming at minimizing order picking path are proposed.Material clustering is transformed into the optimal segmentation problem of undirected graph based on the spectral graph theory,a material association mining algorithm based on Spectral Clustering(SC)is designed.Finally,compared with two optimization methods based on COI rule and original random method,the validity of this method is verified.The results show that the method can shorten the order picking path,reduce the occupancy and selection of order.(3)Outbound and inbound location optimization method based on differential evolution is proposed.In the partition storage environment based on material correlation degree,in order to improve the overall operation efficiency of the order and speed up the speed of the order out of the warehouse,through the analysis of the single order picking time and the overall operation time of the order,the paper puts forward the outgoing batch and the optimization model of the outbound and inbound location decision with the goal of picking operation balance and efficiency optimal.The optimization algorithm based on Differential Evolution(DE)is designed.Based on the basic framework of DE,a mapping method of floating point coding with order cargo and batch integer coding is proposed,and the coding mechanism to satisfy the model constraints is established.Finally,an algorithm parameter optimization strategy is given,and the population size,mutation operator,crossover operator and other algorithm control parameters are made.By designing different order scale cases and comparing with particle swarm optimization operation efficiency,the validity of the model and algorithm is verified.(4)Development and application of location decision system for typical warehousing operationBy encapsulating the model and algorithm to become the optimization service component of the location decision,then based on the MVC design pattern,completed the development of the location decision system,and carried out the system function module application test.The test results show that the basic work functions run normally and meet the expected development requirements.At the same time,the system has been effectively applied in the enterprise and has achieved good results.