Integrated Scheduling Considering AGV Conflict-Free Path Planning In Automated Container Terminal

With the development of economic globalization and international trade,the international shipping market has also developed rapidly.As the main transportation mode for international shipping,container traffic has grown rapidly.In order to meet the growing demand for container transportation,it is important to improve the efficiency of automated container terminals.In automated container terminals,efficiently scheduling quay cranes(QCs),automated guided vehicles(AGVs),automated stacking cranes(ASCs)and path planning for AGVs have been two importation problems.This paper studies the combined optimization problem of "QC-AGV-ASC" integrated scheduling and AGV conflict-free path planning in the synchronous loading and unloading operation mode of automated container terminals.First of all,it sorts out the concept,development status and advantages of automated container terminals.And it lists the operation equipments and operation models of the automated container terminal.The characteristics of the "QC-AGV-ASC" operating system based on synchronous loading and unloading operation mode are analyzed,and establishes theoretical foundation for subsequent study.Secondly,based on the synchronous loading and unloading operation mode and the AGV unidirectional single-lane running road network,combined with the characteristics of the "QC-AGV-ASC" operating system.A bi-level programming model for the "QC-AGV-ASC" integrated scheduling and AGV path planning combination optimization problem is established.Among them,the upper model is the integrated scheduling model of QC,AGV and ASC,the goal is to minimize the maximum makespan of all containers.The lower model is the path planning model of AGV,the goal is to minimize the travel distance of AGV.According to the characteristics of the model,a bi-level programming algorithm based on conflict resolution strategy is designed.Among them,the upper algorithm module is an improved adaptive genetic algorithm,which introduces tabu list,catastrophe and elitism preservation strategy in adaptive genetic algorithm.The purpose is to prevent algorithm from cyclic search and avoid premature convergence,which is used to solve the problem of integrated scheduling of QC,AGV and ASC.The lower algorithm module is a path planning algorithm based on the conflict resolution strategy,and the waiting strategy is adopted as a conflict resolution strategy to solve the conflict-free path planning problem of the AGV.The validity of the model and the effectiveness of the bi-level programming algorithm based on the conflict resolution strategy are verified by experiments.Thirdly,on the basis of the research work,considering the trade-off between operation efficiency and energy consumption of QC,AGV and ASC,as well as the more complicated AGV bidirectional single-lane road network.A bi-level programming model for the "QC-AGV-ASC" integrated scheduling and AGV path planning combination optimization problem,which considering energy consumption is established.The upper model is an integrated scheduling model of QC,AGV and ASC.The goal is to minimize the total operation time and total operation energy consumption of QC,AGV and ASC.The lower model is the path planning model of AGV,and the goal is to minimize travel distance of AGV.According to the characteristics of the model,a bi-level programming algorithm based on time window is designed.Among them,the upper algorithm module is an improved chaotic particle swarm algorithm,which introduces dynamic adjustment learning factor,inertia weight nonlinear decrement strategy and chaotic search in the standard particle swarm optimization algorithm to improve the search ability and convergence ability of the algorithm,and used to solve the integrated scheduling problem of QC,AGV and ASC.The lower algorithm module is path planning algorithm based on time window.The waiting strategy and the re-planning path strategy are used as conflict resolution strategies to solve the AGV conflict-free path planning problem.The rationality of the model and the effectiveness of the bi-level programming algorithm based on time window are verified by experiments.