关键词: 自动化集装箱码头, 自动导引小车（AGV）, 耦合模型, 多学科变量耦合优化设计, 遗传算法

Abstract:

Aiming at the congestion of the horizontal transportation area of the automated terminal caused by the large number of Automated Guided Vehicles（AGVs）, the multi-disciplinary variable coupling optimization design method is used to study the AGV scheduling and AGV configuration of the automated terminal. Firstly, the AGV scheduling model is established with the goal of minimizing the shore waiting time, and then the AGV configuration model is established with the goal of minimizing the number of AGVs. The two models are connected with the completion time and the number of AGV as common design variables, and a coordinated scheduling coupling model is established. The design example is used to solve the coupled model by using the fast convergence function of Genetic Algorithm（GA）. After repeated iterative calculation, the optimal AGV number and AGV scheduling scheme are obtained. Finally, the scale of the study is expanded, and nine sets of experiments are designed. The results of GA, Particle Swarm Optimization（PSO） and Ant Colony Optimization（ACO） are compared. The results show that with the increase of the scale of the example, the ability to solve GA is more prominent, which verifies the feasibility of the algorithm designed in this paper.

Key words: automated container terminal, Automated Guided Vehicle（AGV）, coupling model, multidisciplinary variable coupling optimization design, genetic algorithm