A simulation-based vessel-truck coordination strategy for lighterage terminals. (October 2018)

• Record Type: Journal Article
• Authors: Zhou, Chenhao; Li, Haobin; Lee, Byung Kwon; Qiu, Zhipeng
• Is Part Of: Transportation research. Volume 95(2018)
• Page Start: 149
• Page End: 164
• Publication Date: 2018-10
• Subjects: Lighterage terminals -- Simulation-based approach -- Schedule coordination -- Congestion reduction; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2018.07.015
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: The operation process of a real-world lighterage terminal is analysed. A coordination strategy is proposed to reduce congestions of vessels and vehicles. A simulation-based approach identifies the optimal setting for the strategy. Discrete-event simulation and bi-objective simulation optimization are applied. The congestion reduction is significant from the numerical experiment. A mobile application prototype is proposed for real-world implementation. Abstract: Lighterage contributes significantly to the maritime industry since thousand tons of necessary supplies have to be delivered to mother vessels anchored near sea every day. A single lighter waits to receive cargoes from multiple suppliers at the berth, while the trucks wait for their turns to enter the terminal. Due to the limited space, the terminal operation becomes vulnerable to the lack of coordination of their arrivals. In this study, despite a traditional industry, we are interested in applying the emerging technologies to improve the operation efficiency. We develop a simulation-based coordination strategy to construct coordinated schedules for both the lighters and suppliers to reduce congestions in the lighterage terminal The discrete event simulation model is developed based on understanding the real-world terminal in Singapore, and the controlled arrival method, determining coordinated arrival schedules of trucks, is introduced and embedded to the simulation model. The simulation model is tuned up with a benchmark setting of 6-month historical data. To find the optimal strategy, an advanced bi-objective simulation optimization algorithm is employed. According to our findings, the proposed strategy could significantly improve the efficiency of both lighters and trucks in various indicators. At the end, a mobile application prototype is proposed to deliver the coordinated schedules to different parties, and improve the communication between parties.