An Optimization Model Of AGV Scheduling And Storage Location Allocation For Automated Terminal Considering Uncertainty

With the increasingly fierce port competition and the rapid development of artificial intelligence technology,port automation has become an important trend of port development at home and abroad.Compared with the traditional wharf,the automated wharf can steadily and reliably improve the passing capacity and service level of the wharf and reduce the operating cost.Automatic dock operation scheduling and intelligent decision has become a hot issue in the field of port logistics,and the horizontal transportation scheduling problem is one of the key problems in the study of automatic wharf job scheduling.The AGV(automatic guidance vehicle)serves as the main horizontal transport equipment for containers between the wharf front and the storage yard.The core issue of AGV scheduling is to ensure that the quayside bridge and the field bridge junction are reached within the specified time and the horizontal handling task is completed.Compared with traditional card set scheduling,AGV scheduling has different characteristics.It should not only consider reasonable connection with quay bridge and field bridge,but also consider whether congestion and deadlock occur during operation.In this context,the optimization of AGV task assignment and container storage location considering the uncertain running time is studied.In this paper,the problem of cooperative scheduling between AGV task allocation and container storage location is studied under the condition of considering congestion.With the goal of minimizing the completion time of the maximum quayside bridge task,according to the number of vehicles in the AGV's driving path,the congestion in the path is abstracted into the congestion coefficient,and the AGV scheduling and storage location optimization model is constructed.The OPL language in ILOG CPLEX software was used to solve this problem and the effectiveness of the heuristic algorithm in solving AGV scheduling problem was verified.Secondly,add the uncertainty of operation time and other constraints.Considering the different congestion conditions of AGV in the path,determine the most satisfactory,most possible and most negative time for AGV operation.Establish a multi-objective scheduling optimization model with the goal of minimizing the quayside delay risk and minimizing the AGV operation time.With the help of solving software,the validity of the model can be verified.Meanwhile,the feasibility and advantages of heuristic algorithm can be verified by comparing the exact results of calculation examples of different sizes with the results of heuristic algorithm.With the help of solving software,the validity of the model can be verified.Meanwhile,the feasibility and advantages of heuristic algorithm can be verified by comparing the exact results of calculation examples of different sizes with the results of heuristic algorithm.In this,paper,the layout of an automatic container terminal in China is selected as the background,and relevant data in the experiment are set.The calculation results show that the AGV task allocation and storage location allocation are integrated for scheduling,and the scheduling plan obtained can balance the operation time of AGV.By taking into account the uncertainty of the running time,AGV operation time is again reduced and AGV congestion paths are avoided.The algorithm in this paper can efficiently obtain the scheduling scheme of the actual scale calculation example,so as to meet the requirements of production operations.In addition,considering the uncertain operation time in this paper,it is helpful to improve the stability of the automated wharf system and meet the development needs of the automated wharf.