Research on Collaborative Scheduling Optimization of Rail-mounted Granty Crane and AGV in the on-Dock Rail

Abstract

Proper dispatching of equipment at the automated terminal in the on-dock rail can reduce energy consumption during loading and unloading, which is significant for the green development of terminals. This paper studies the collaborative scheduling of rail-mounted gantry cranes (RGCs) and automated guided vehicles (AGVs) for on-dock rail. Firstly, this problem is considered with the allowable operating time window of trains and ships, safety margin between the RGCs, heavy load and no-load of AGV, and the waiting time of RGC and AGV. Furthermore, the collaborative scheduling model is established, which takes the minimum energy consumption of RGC and AGV. Self-adaptive chaotic genetic algorithm is designed to solve the model. Finally, experiments were designed to analyze the effects of the number of containers, the delayed arrival time of vessels, and the proportion of dockside containers on the energy consumption of RGCs and AGVs. The results show that the total energy consumption of RGCs and AGVs is the smallest when the number of rail-mounted gantry cranes and AGVs is 1:4. In addition, the number of AGVs should be decreased with the increase of ship delay time and the proportion of quayside containers to reduce energy consumption.