Research On Optimization Algorithm And System Of Warehouse Operation In Warehouse Logistics

The management of warehousing and logistics is a field with a long history.In recent years,the focus on warehousing performance and overall logistics performance has gradually increased,mainly including the following three aspects: streamlined supply chain separation requires reduced inventory and shorter response time for warehousing operations;More and more suppliers are managing larger and more complex warehouses,with multiple customers and varying needs;the number of online retailer transactions is rapidly increasing,and the orders of end customers are directly managed by the warehouse.In various operations of the warehouse,the reasonable allocation of cargo spaces and job picking seriously affect the performance of the entire warehouse,accounting for about 55% to 75% of the total storage cost.Therefore,the reasonable allocation of cargo space and job picking are priorities for improving the company's logistics capabilities.In order to be able to closely integrate the needs of the enterprise with the development of actual technology,a mathematical optimization model will be proposed for the cargo location operation problem,and the advantages of intelligent algorithms will be used to study the optimal allocation of practical problems.Finally,the implementation of the storage system will be studied.Therefore,the research contents of this article include the following:(1)Research on cargo space optimization algorithm based on Lagrange interpolation hybrid differential evolution algorithmIn order to improve the efficiency of warehousing operations,a location allocation model based on resource conditions of picking trolley running time,shelf stability,and storage capacity of the location is constructed.At the same time,each item in each batch of orders is allocated to the corresponding zone.The maximum completion time of the optimal location is the target model for batch re-allocation of orders with resource conditions,and the combined model obtained by cascading the two models is solved by an algorithm.This paper proposes an improved differential evolution algorithm thatincorporates Lagrangian interpolation.The improved differential evolution algorithm increases the local and global automatic switching thresholds to ensure that based on the standard differential evolution algorithm,the search for the optimal individual near each generation is increased.Optimal ability,while making the algorithm's population disturbance degree automatically switch between global and local through certain conditions.The improved algorithm ensures the population diversity of the algorithm by adaptively adjusting the cross-probability factor,and avoids the premature and unconvergent phenomena of the algorithm.Finally,a comparison experiment of multiple algorithms will be performed by setting different experimental schemes,and the final results will be compared for performance.(2)A collaborative planning algorithm for multiple picking cart paths for storage operations based on multi-frame time window rotationIn this paper,a static optimal trajectory is planned by combining a graph theory algorithm,and then the discrete points of the static trajectory are mapped to the control points of the B-spline through the features of segmentable control and multi-segment continuity of the B-spline The rotation of the frame time window,the model is solved in each frame time window,and the method of updating the step size by using Newton's iterative fusion backtracking method is continuously updated to iterate the kinematic control points of the car in each frame time window,and finally the overall A collection of dynamic track points.The model of the proposed algorithm is based on the constraints of the geometry and kinematics of multiple picking carts in the storage environment,and the minimum integral of the first-order norm of the dynamic position state of each frame to the end position state of each frame is used as the objective function.,Establish a function objective model with convex set features.In order to prevent the picking trolley from colliding during the movement,an anti-collision constraint of the picking trolley is introduced,and the collision avoidance constraint is combined with the B-spline characteristics to realize the mapping of constraints and B-spline characteristics.Finally,an obstacle model for the storage environment is established,and the effectiveness of the proposed model and algorithm is verified by designing collaborative path planning experiments for different numbers of picking trolleys.(3)Development of a prototype warehouse management system for practical applicationsBy analyzing the business process and data process of the actual warehouse management,the development of a prototype system based on the Web-based layered thinking.The database table is established through the mapping relationship between data entities and objects,and the powerful entity object mapping capability of the Mybatis framework is used to connect with the object mapping module of the Spring framework.Based on the complete function modules of the Spring framework and the strong ability to integrate other technical modules,Spring will integrate Spring MVC and Mybatis frameworks to develop the warehousing service module.Using Spring's IOC ideas,all service module components will be delivered to the container for maintenance,and the Web The components are handed over to SpringMVC's IOC container maintenance.The framework-based thinking makes the development logic of the entire service component simple.The practicality and stability of the developed system are verified by designing actual test cases.