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Berth allocation recovery for container transshipment terminals.

Authors :
Lv, Xiaohuan
Jin, Jian Gang
Hu, Hao
Source :
Maritime Policy & Management. Jun2020, Vol. 47 Issue 4, p558-574. 17p.
Publication Year :
2020

Abstract

In container terminals, operators normally form an initial plan for berth allocation before the arrival of incoming vessels. However, during the real operations, unforeseen incidents (e.g. delays, equipment breakdowns) happen frequently, which hinder the implementation of initial plans. In response to disruptions, terminal operators usually employ an experience-based strategy for berth allocation recovery. However, this practice may not work well in challenging situations, especially when extensive transshipment operations need to be conducted, and the berthing for mother and feeder vessels should be coordinated. This paper studies the disruption recovery problem for berth allocation in transshipment terminals, and develops decision support tools for terminal operators. A mixed integer linear programming model is established to adjust original berthing plan with the objective of minimizing recovery cost caused by deviations from the original plan. Quay crane assignment decision is also taken into account during disruption recovery. Transshipment connections between correlated feeder and mother vessels are also considered specifically in order to reduce the missing of transshipment connection opportunities. Squeaky Wheel Optimization heuristic is devised to find near-optimal solutions under large problem scales. Extensive computational experiments validate the effectiveness and the efficiency of designed method, and the results show practical benefit from incorporating transshipment consideration when rescheduling berth allocation. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
03088839
Volume :
47
Issue :
4
Database :
Academic Search Index
Journal :
Maritime Policy & Management
Publication Type :
Academic Journal
Accession number :
144283100
Full Text :
https://doi.org/10.1080/03088839.2020.1725672