SGICT Builds an Optimization-Based System for Daily Berth Planning

Yi Ding (), Shuai Jia (), Tianyi Gu () and Chung-Lun Li ()
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Yi Ding: Logistics Research Center, Shanghai Maritime University, Shanghai 200135, China
Shuai Jia: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong
Tianyi Gu: Department of Computer Science, University of New Hampshire, Durham, New Hampshire 03824
Chung-Lun Li: Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong

Interfaces, 2016, vol. 46, issue 4, 281-296

Abstract: In container terminal operations, the allocation of berth-side resources to serve calling vessels is called berth planning. For each vessel, berth planning generally involves determining the time interval for berth stay (i.e., berthing and departure times and the handling of start and end times), the berthing position along the quay, and the number of quay cranes that will be dedicated to handle it. The objectives are to maximize the vessel service levels (i.e., minimize the departure lateness) and minimize operating costs during a planning horizon. In this paper, we describe the implementation of an operations research-based solution at Shanghai Guandong International Container Terminal (SGICT), one of the largest container terminals at the Port of Shanghai, to optimize its daily berth planning. We embed our solution into a decision support system (BAPOPT), which provides SGICT’s planners with effective and executable berth plans. Using BAPOPT, SGICT expects to improve its vessel-handling productivity by at least 15 percent. With the support of BAPOPT, SGICT has started shifting its operational emphasis from reactive real-time dispatching to proactive resource planning, helping to relieve its operations department from a considerable amount of tedious work and improve the efficiency of its planning department.

Keywords: container terminal optimization; berth allocation; quay crane allocation; decision support system (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (9)

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