Research On Layout Optimization And Multi-AGV Dynamic Scheduling Method For Intelligent Storage

With the deep integration of Internet technology with production and life,the e-commerce is developing rapidly.The intelligent storage system emerges at the right moment.How to improve the efficiency of warehouse logistics has become a research hotspot at present.Due to the characteristics of modern warehouse logistics such as the large volume,variety and short cycle of goods,the widely used multi-AGV automatic sorting system is subject to congestion,deadlock and conflict.Its efficiency is increasingly difficult to meet the current needs of warehousing and logistics.To solve this question,the layout optimization of intelligent storage system and the collaborative optimization method of multi-AGV task allocation and path planning are studied.The main contents are as follows:Firstly,it studies the optimization method of shelf layout of intelligent storage system.This paper adopts topological map method to model the environment map and analyzes the influence of warehouse shelf layout on intelligent warehouse logistics.Based on the complex network theory,an optimization algorithm of warehouse shelf layout based on the number of edges and nodes is proposed.The experimental results show that compared with traditional warehouse shelf layout method,this algorithm can effectively reduce the deadlock rate of multi-AGV system,so as to improve the efficiency of intelligent warehouse logistics system.Secondly,it studies the cooperative optimization method of multi-AGV task allocation and path planning.Firstly,this paper introduces the multi-AGV path planning model based on network flow theory.On this basis,a collaborative optimization model of task allocation and path planning is proposed,and the model is solved by integer linear programming method.It establishes constraints and objective functions for node conflicts and edge conflicts,and uses the branch-and-bound method to find the optimal solution of multi-AGV joint optimization problem,so that each AGV can match the most suitable task order and make appropriate path selection.In addition,the multiAGV collaborative dynamic scheduling method based on the event-triggering mechanism is further studied,and the branch and bound method of integer linear programming is used to solve it.This method enables the system to independently set the trigger nodes,timely consider the new task orders and make reasonable planning,reduce the task completion time of the multi-AGV system,and improve the system scheduling efficiency.Finally,the multi-AGV scheduling simulation platform based on Python is developed.The central controller module,map module,task scheduling module,multi-AGV simulation module and obstacle simulation module of the simulation platform are designed.It lays a foundation for the subsequent research on multi AGV scheduling.The research content of this paper is of great significance to the actual intelligent storage layout design and multi-AGV scheduling efficiency improvement.It can provide theoretical guidance and technical support for the further optimization of intelligent storage system...