Research On Path Design And Scheduling Of Warehouse Intelligent Automated Guided Vehicle

With the rapid development of economy and internet,the scale of online shopping is increasing.For the e-commerce enterprises,tens of thousands of orders will arrive every hour during peak hours,which is a huge challenge to process orders.Customer demand has gradually led to a shift in the order structure to small and multiple batches,while the size of distribution centers has become larger and larger as the variety and quantity of goods have increased.Under the requirement of the contemporary market environment,whether the distribution center can quickly select the right goods under the right conditions and deliver them to customers in time is of vital importance.Under the background of the rapid development of e-commerce industry,this thesis studies the intelligent AGV scheduling problem in distribution centers using the "goods to people" picking mode.Firstly,this thesis extracts scientific problems from the actual operation of warehouse,summarizes the relevant literature on the AGV scheduling problem under the "goods to people" picking mode.Then the composition and layout of the intelligent warehouse are analyzed,and the operation process of the intelligent warehouse is sorted out.On this basis,there are two core problems: AGV path planning problem and AGV collision avoidance problem.The solution idea and two-stage optimization method are put forward.The two-stage optimization method firstly carries out path planning for AGV,uses mathematical modeling and time-priority-based path generation algorithm to generate the initial path,and then joins collision avoidance algorithm to detect possible collision path points and adjust them,an efficient and feasible global AGV scheduling scheme is obtained.Finally,different size warehouse layout and order requirements are constructed,which proves the efficiency and adaptability of the two-stage algorithm for AGV scheduling problem.Considering the operation and cost,the sensitivity of AGV quantity is discussed with the result of the algorithm solution,and the optimal AGV quantity allocation proposal is obtained.