A Collaborative Berth Planning Approach for Disruption Recovery
Traditionally, terminal operators create an initial berthing plan before the arrival of incoming vessels. This plan involves decisions on when and where to load or discharge containers for the calling vessels. However, disruptive unforeseen events (i.e., arrival delays, equipment breakdowns, tides,...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Open Journal of Intelligent Transportation Systems |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9709595/ |
| _version_ | 1828084139503386624 |
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| author | Xiaohuan Lyu Rudy R. Negenborn Xiaoning Shi Frederik Schulte |
| author_facet | Xiaohuan Lyu Rudy R. Negenborn Xiaoning Shi Frederik Schulte |
| author_sort | Xiaohuan Lyu |
| collection | DOAJ |
| description | Traditionally, terminal operators create an initial berthing plan before the arrival of incoming vessels. This plan involves decisions on when and where to load or discharge containers for the calling vessels. However, disruptive unforeseen events (i.e., arrival delays, equipment breakdowns, tides, or extreme weather) interfere with the implementation of this initial plan. For terminals, berths and quay cranes are both crucial resources, and their capacity limits the efficiency of port operations. Thus, one way to minimize the adverse effects caused by disruption is to ally different terminals to share berthing resources. In some challenging situations, terminal operators also need to consider the extensive transshipment connections between feeder and mother vessels. Therefore, in this work, we investigate a collaborative variant of the berth allocation recovery problem which focuses on the collaboration among terminals and transshipment connections between vessels. We propose a mixed-integer programming model to (re)-optimize the initial berth and quay crane allocation plan and develop a Squeaky Wheel Optimization metaheuristic to find near-optimal solutions for large-scale instances. The results from the performed computational experiments, considering multiple scenarios with disruptive events, show consistent improvements of up to 40% for the suggested collaborative strategy (in terms of costs for the terminal operators). |
| first_indexed | 2024-04-11T04:19:19Z |
| format | Article |
| id | doaj.art-479d838dd34442b1be8e5a6923cb4f2a |
| institution | Directory Open Access Journal |
| issn | 2687-7813 |
| language | English |
| last_indexed | 2024-04-11T04:19:19Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Open Journal of Intelligent Transportation Systems |
| spelling | doaj.art-479d838dd34442b1be8e5a6923cb4f2a2022-12-31T00:02:07ZengIEEEIEEE Open Journal of Intelligent Transportation Systems2687-78132022-01-01315316410.1109/OJITS.2022.31505859709595A Collaborative Berth Planning Approach for Disruption RecoveryXiaohuan Lyu0Rudy R. Negenborn1Xiaoning Shi2Frederik Schulte3Department of Maritime and Transport Technology, Delft University of Technology, CD Delft, The NetherlandsDepartment of Maritime and Transport Technology, Delft University of Technology, CD Delft, The NetherlandsInstitute of Transport Research, German Aerospace Center, Berlin, GermanyDepartment of Maritime and Transport Technology, Delft University of Technology, CD Delft, The NetherlandsTraditionally, terminal operators create an initial berthing plan before the arrival of incoming vessels. This plan involves decisions on when and where to load or discharge containers for the calling vessels. However, disruptive unforeseen events (i.e., arrival delays, equipment breakdowns, tides, or extreme weather) interfere with the implementation of this initial plan. For terminals, berths and quay cranes are both crucial resources, and their capacity limits the efficiency of port operations. Thus, one way to minimize the adverse effects caused by disruption is to ally different terminals to share berthing resources. In some challenging situations, terminal operators also need to consider the extensive transshipment connections between feeder and mother vessels. Therefore, in this work, we investigate a collaborative variant of the berth allocation recovery problem which focuses on the collaboration among terminals and transshipment connections between vessels. We propose a mixed-integer programming model to (re)-optimize the initial berth and quay crane allocation plan and develop a Squeaky Wheel Optimization metaheuristic to find near-optimal solutions for large-scale instances. The results from the performed computational experiments, considering multiple scenarios with disruptive events, show consistent improvements of up to 40% for the suggested collaborative strategy (in terms of costs for the terminal operators).https://ieeexplore.ieee.org/document/9709595/Collaborative berth planningdisruption recoverymixed-integer programmetaheuristic |
| spellingShingle | Xiaohuan Lyu Rudy R. Negenborn Xiaoning Shi Frederik Schulte A Collaborative Berth Planning Approach for Disruption Recovery IEEE Open Journal of Intelligent Transportation Systems Collaborative berth planning disruption recovery mixed-integer program metaheuristic |
| title | A Collaborative Berth Planning Approach for Disruption Recovery |
| title_full | A Collaborative Berth Planning Approach for Disruption Recovery |
| title_fullStr | A Collaborative Berth Planning Approach for Disruption Recovery |
| title_full_unstemmed | A Collaborative Berth Planning Approach for Disruption Recovery |
| title_short | A Collaborative Berth Planning Approach for Disruption Recovery |
| title_sort | collaborative berth planning approach for disruption recovery |
| topic | Collaborative berth planning disruption recovery mixed-integer program metaheuristic |
| url | https://ieeexplore.ieee.org/document/9709595/ |
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