Load-In-Load-Out AGV Route Planning in Automatic Container Terminal

Abstract

Efficient automatic guided vehicle (AGV) scheduling is the key to increase the throughput of automated container terminals. Traditional transport strategies cannot guarantee that AGVs are fully loaded during their traveling between the dock and the container yard, which leads to the insufficient utilization of AGVs. A load-in-load-out AGV route planning mode provides two-way loading between the dock and the container yard and thus improves the efficiency of container terminals. In this paper, a load-in-load-out AGV route planning model is designed with the help of a buffer zone where an AGV can carry at most two containers. A simulated annealing algorithm is used to solve it. Comparisons with the popular generic algorithm and particle swarm algorithm are made. Simulated results show that the proposed algorithm can effectively solve the problem and realize the bi-directional loading of AGVs, which is of great significance to improve the efficiency of the production of automated container terminals.

An Improved DQN Algorithm for Automated Guided Vehicle Pathfinding Problem in Port Environment

“…Meng Long Cao et al [24] studied the path planning problem of AGVs in automated container terminal loading and unloading processes, achieving a reduction in distance travelled by modifying the classical particle swarm optimisation algorithm. Yixiang Xu et al [25] introduced buffer zones to address the problem of low loading rates of conventional AGVs, solving the AGV path planning problem using a simulated annealing algorithm. Peixiu Han et al [26] proposed an improved algorithm for the artificial bee colony algorithm by introducing the ideas of genetic algorithm and adaptive factor.…”

A goal-programming based optimal port docking scheme under COVID-19

“… Ma et al (2020) established a mathematical model for the operation of multi load AGV in the automatic container terminal with the minimum moving distance as the goal, and used a mutation frog jump algorithm based on priority rules to solve it, which is of great significance to improve the operational efficiency. Xu et al (2020) pointed out that efficient AGV scheduling is the key to improving the throughput of automated container terminals, and the realization of two-way loading of AGV can significantly improve the port handling efficiency. Consequently, an AGV path planning model for cargo loading is constructed and solved by a simulated annealing algorithm.…”

Digital Twin for Automatic Transportation in Industry 4.0

“…Due to the use of new technologies, AGV routes have been automated by creating customized missions [ 54 ]. In the context of DTs, simulation interfaces are not sufficiently discussed in the current literature.…”