Scheduling quay cranes and shuttle vehicles simultaneously with limited apron buffer capacity. (March 2023)

• Record Type: Journal Article
• Authors: Yin, Yu-Qi; Zhong, Meisu; Wen, Xin; Ge, Ying-En
• Is Part Of: Computers & operations research. Volume 151(2023)
• Publication Date: 2023-03
• Subjects: Container terminal -- Quay crane -- Shuttle vehicle -- Integrated scheduling problem -- Mixed-integer linear programming; QC Quay crane -- SV Shuttle vehicle -- AGV Automated guided vehicle -- ALV Automated lifting vehicle -- HTD Horizontal transport device -- YC Yard crane -- YT Yard truck -- ASC Automated stacking crane -- MILP Mixed-integer linear programming -- SIA Sequential insertion algorithm -- GIA Greedy insertion algorithm -- GA Genetic algorithm -- QCSP Quay crane scheduling problem; Operations research -- Periodicals; Electronic digital computers -- Periodicals; 004.05
• DOI: 10.1016/j.cor.2022.106096
• Languages: English
• ISSNs: 0305-0548

Abstract

Abstract: How to schedule quay cranes (QCs) and shuttle vehicles (SVs) simultaneously or model them in an integrated scheduling problem is one of the most important problems in operations and management of a container terminal. This paper investigates an integrated QC and SV scheduling problem constrained by apron buffer capacity. In this problem, the decisions to make include the bay-to-QC assignment, the QC-bay sequence, the QC-job sequence, the job-to-SV assignment and the SV-job sequence. First, a mixed-integer linear programming model is formulated for this problem to minimize the makespan. Second, the relationships and interactive variables among the four segments of constraints of the proposed model (i.e., scheduling QCs for vessel bays, sequencing jobs handled by a QC in each bay, scheduling SVs for jobs, apron buffer capacity constraints for each vessel bay) are analyzed to present three rules: vessel block rule, near-to-far rule and full-buffer rule. Finally, a sequential insertion algorithm, a greedy insertion algorithm and an improved genetic algorithm are proposed to solve mid- and large-sized cases for the problem. Numerical experiments show that the algorithms perform well, compared to the off-the-shelf solver. Based on these experiments, managerial implications are discussed for container terminal operations and management.