Multi-Objective Real Time Location Decision Optimization For Dense Warehouse

In recent years,the development model of my country’s warehousing industry has encountered a bottleneck,and digitalization and intelligence are becoming the core driving force for the high-quality development of the industry.The dense warehouse management and control system has effectively improved the degree of automation and reduced labor costs and land costs through functions such as intelligent location decision-making,automatic handling,intelligent monitoring,and multi-equipment coordination scheduling,and has become an efficient,energy-saving,and low-cost System construction plan.Among them,the decision optimization of warehouse location is an important link to improve the efficiency of intensive warehouse management and control work.Due to the characteristics of dynamic changes in warehousing operations,equipment,inventory and other entities,how to make reasonable decisions on warehouse locations,respond to dynamic constraints of the warehousing environment in real time,and meet the needs of efficient and energy-saving warehousing has attracted extensive attention from industry and academia.The traditional warehousing management and control system still has the problems of weak intelligent level of warehouse location decision-making and insufficient business integration capabilities,and the special type of industrial software for warehousing location decision-making is strong,which cannot meet large-scale and diversified warehouse needs.In response to the above problems,the rapid development of Internet technology,database technology and intelligent technology provides technical support for the realization of networked and intelligent warehouse location decision functions and the development of industrial software.Therefore,it is of great significance to study the optimization method of location decision-making and its application to improve the quality and efficiency of warehousing operations and promote the application of key technologies for intelligent warehousing.The main research contents are as follows:(1)Established an information model for multi-objective optimization of warehouse location decisionsIn response to the multi-objective real time location decision optimization problem,the dynamic inventory status,dynamic equipment status,pallet utilization,and shelf occupancy are considered.The communication module is used to screen the location variables in real-time,and an optimization model based on the objectives of the shortest path,shelf center of gravity stability,job equal distribution,and low energy consumption is established.To optimize the shortest path sub-objective function,an improved A*algorithm is introduced,which responds to dynamic constraints in real-time and obtains paths and their evaluation costs that better match the actual dynamic environment of the warehouse.At the same time,based on the attributes of entities such as jobs,locations,pallets,materials,and shelves,as well as the relationships between entities,an E-R diagram is established and analyzed,and an entity class and relational database mapping model are then built to provide the basis for data access and storage for the multiobjective location decision algorithm.(2)Designed a warehouse location decision algorithm based on adaptive differential evolutionAiming at the multi-objective location decision optimization model,a differential evolution algorithm is designed to solve it.Firstly,the floating-point number of 0～1 is used to encode the location variable,and the mapping relationship between the location variable and the evolutionary individual vector is established,and the corresponding target location is obtained by decoding according to the feasible domain of the dynamic location.Secondly,in order to overcome the blindness of the algorithm search in the process of location decision,an adaptive scaling factor is used to improve the search efficiency and quality of the algorithm to meet the real time requirements of location decision.At the same time,because there are conflicts among the sub-objectives of the optimization model,it is impossible to obtain the optimal solution for each sub-objective function value.Therefore,a differential evolution algorithm based on Pareto optimization is designed,and the weights of sub-objective functions are obtained by AHP,and the comprehensive evaluation value of multiple objective functions is obtained based on this,and then the optimal solution is selected from the Pareto solution set.Finally,multiple batches of jobs are designed for experimental analysis.The results show that compared with the differential evolution algorithm for single-objective optimization,the differential evolution algorithm based on Pareto optimization has a significant optimization effect on energy consumption targets,and the optimization rate is about 15% to 20%.between.At the same time,the time of location decision is controlled within 300 milliseconds,which can effectively meet the real time requirement of location decision.(3)Web-based warehouse location decision visualization and its application integrationBased on the enterprise’s intensive warehouse test platform,design and develop the warehouse management and control system.In order to meet the requirements of system flexibility,scalability and scalability,using the ASP.NET development framework and SQL Server database technology,based on the service-oriented architecture,the microservice components and Web API interface of the warehouse location decision function are designed.The client application program is built in the MVC mode,the UI model of the Web front-end interface is designed,and the Web visualization functions such as job setting and intelligent location decision are realized.Through the on-site application test of the enterprise,the developed system can effectively realize the decision function of location.Through the above research work,the multi-objective warehouse location decision function based on evolutionary intelligence has been realized,the application service interface for warehouse location decision has been developed,and the Web visualization interface for warehouse location decision has been developed,which has been verified by practical application in enterprises,effectively improving the allocation efficiency and operation quality of warehouse resources,and providing a reference technical basis for supporting efficient and energy-saving warehouse.