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Berth and quay-crane allocation problem considering fuel consumption and emissions from vessels


Hu, Q-M and Hu, Z-H and Du, Y, Berth and quay-crane allocation problem considering fuel consumption and emissions from vessels, Computers & Industrial Engineering, 70 pp. 1-10. ISSN 0360-8352 (2014) [Refereed Article]

Copyright Statement

Copyright 2014 Elsevier Ltd.

DOI: doi:10.1016/j.cie.2014.01.003


Resolving the berth and quay-crane allocation problem improves the efficiency of seaside operations by optimally allocating berthing spaces and quay cranes to vessels, typically by considering a vesselís sailing speed and arrival time at a port as constant parameters, while ignoring the impact of arrival times on fuel consumption and emissions when sailing. This work applied a novel nonlinear multi-objective mixed-integer programming model that considered a vesselís fuel consumption and emissions, and then transformed this model into a second-order mixed-integer cone programming model to solve the problemís computational intractability. Furthermore, the impact of number of allocated quay cranes on port operational cost, and a vesselís fuel consumption and emissions was analyzed. Additionally, a vesselís emissions while moored are also calculated based on wait time. Experimental results demonstrate that the new berth and quay-crane allocation strategy with a vesselís arrival time as a decision variable can significantly improve vesselsí fuel consumption and emissions, the air quality around ports and utilization of berths and quay cranes without reducing service quality.

Item Details

Item Type:Refereed Article
Keywords:berth and quay crane allocation problem, fuel consumption, emission, second-order cone programming, nonlinear optimization
Research Division:Commerce, Management, Tourism and Services
Research Group:Transportation, logistics and supply chains
Research Field:Maritime transportation and freight services
Objective Division:Transport
Objective Group:Water transport
Objective Field:Port infrastructure and management
UTAS Author:Du, Y (Dr Bill Du)
ID Code:113328
Year Published:2014
Web of Science® Times Cited:63
Deposited By:Maritime and Logistics Management
Deposited On:2016-12-21
Last Modified:2018-04-11

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