Research On Task Scheduling Optimization Of Auto Store Dense Storage System Considering Container Removal Operation

After entering the information age,my country’s e-commerce and other industries have developed rapidly,and the warehousing and logistics industry is facing greater pressure.It is necessary to improve warehousing capacity without increasing warehousing area.In June and September 2020,the National Development and Reform Commission issued relevant documents to vigorously promote new logistics technology and equipment such as logistics robots.Based on the above background,this paper selects the Auto Store intensive warehousing system with a high level of automation and intelligence in the warehousing system as the research object.The feature of this system is that the lanes between the shelves and the partitions in the shelves are completely removed,and the three-dimensional shelf structure is directly spliced together to form a similar Rubik’s cube structure,which greatly improves the utilization rate of storage space.The AGV trolley runs on the top of the shelf,and realizes vertical grabbing through its own telescopic device.Compared with other storage systems,the core of AGV scheduling in this system includes two parts,which are the AGV’s scheduling of the target box and the dumping of the obstructing box on the top of the target box.Through the analysis of domestic and foreign literature,there is little research in this direction.Therefore,this paper conducts research on AGV task scheduling considering the operation of dumping.In the aspect of box dumping operation,this paper mainly solves the two problems of who will grab the obstacle box and how to place the obstacle box.In this paper,the same AGV is used to perform the dumping operation of the obstacle box and the extraction of the target box,establish a mathematical model of the dumping operation for the Auto Store system,propose the corresponding dumping strategy,and use MATLAB programming to realize it.The proposed out-of-box strategy is validated.It effectively verifies the applicability and effectiveness of the dynamic optimization strategy in the unpacking operation.In terms of task scheduling,since the unloading operation and the extraction of target boxes are completed by the same AGV,the unloading operation is embedded in the task scheduling model.Through the research and analysis of the current situation of multi-AGV task scheduling,the corresponding task scheduling optimization mathematical model is established and designed to improve First,after screening the difference evaluation factor,the initial solution is more evenly distributed in the solution space,which helps the algorithm to jump out of the local optimum;second,each layer of coding in the multi-layer coding is reversed separately operation,which can effectively improve the local search ability of the algorithm.By designing a standard example and comparing the task scheduling scheme before and after optimization,the effectiveness and feasibility of the algorithm in this paper are effectively verified.In terms of system operation status,it is verified by calculation examples that the total task completion time is positively correlated with task scale,storage three-dimensional scale and plane scale,and is negatively correlated with AGV scale and storage filling rate;The filling rate,storage three-dimensional scale,and plane scale were negatively correlated,positively correlated with task scale,and had nothing to do with AGV scale.