Double-Cycling AGV Scheduling Considering Uncertain Crane Operational Time at Container Terminals

Abstract

Container terminals (CTs) play an important role in the modern logistics and transportation industry. The utilization of automated guided vehicles (AGVs) can be effectively facilitated by reducing their empty running. The existing strategies cannot guarantee the full load of AGVs during their transportation because of the complex constraints of container scheduling. This work proposes a double-cycling AGV scheduling model that ensures a full load of AGVs between the quayside and the yard. The objective is to minimize the total waiting time of AGVs and ensure a high loading rate of AGVs by scheduling loading/unloading containers. Furthermore, it takes the randomness of the quay crane’s operational time into consideration. By assigning a time interval to AGVs’ arrival at a quayside, a container scheduling sequence is obtained based on a Hybrid Particle Swarm Optimization (HPSO) algorithm with a penalty function. Via experiments, it shows that the proposed model can obtain the least number of AGVs for container transportation, minimize AGVs’ total waiting time, and ensure the high loading rate of AGVs.

Scheduling optimization of AGVs in workshop based on cost-efficiency-emission competition mechanism

“…To solve the conflict problem of AGVs, Shi et al 15 proposed a multi-objective scheduling model based on total driving distance and waiting time, and used the A* path planning algorithm to search the shortest path of AGVs. Zhang et al 16 proposed a double-cycling AGV scheduling model, which can guarantee the full load of AGVs during their transportation. A summary of research on AGV scheduling is presented in Table 1 There have been several researches on the AGV scheduling based on a single evaluation standard or multi objective comprehensive evaluation criteria.…”