Double-Cycling AGV Scheduling Considering Uncertain Crane Operational Time at Container Terminals
Source abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Maritime Ports and Logistics · Advanced Manufacturing and Logistics Optimization · Urban and Freight Transport Logistics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Qingdao New Qianwan Container Terminal Company Ltd., Qingdao 266500, China
Funding
National Natural Science Foundation of China · Natural Science Foundation of Shandong Province · Jingying Program of Shandong University of Science and Technology
References (47)
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