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http://hdl.handle.net/10397/98330
| Title: | Daily berth planning in a tidal port with channel flow control | Authors: | Zhen, L Liang, Z Zhuge, D Lee, LH Chew, EP |
Issue Date: | Dec-2017 | Source: | Transportation research. Part B, Methodological, Dec. 2017, v. 106, p. 193-217 | Abstract: | This paper studies an operational-level berth allocation and quay crane assignment problem (daily berth planning) considering tides and channel flow control constraints. An integer programming model is proposed for this problem. Then a column generation solution approach is developed on a set partitioning based reformulation of the original model. Computational study is conducted on 30 test cases constructed from real-world data to validate efficiency of the proposed solution approach. Results show that this simple but practical solution approach can optimally solve the daily berthing planning problem instances with up to 80 vessels, 40 berths, and 120 quay cranes within one hour, which is reasonable and acceptable for the real-world applications. The proposed decision model and the solution approach could be potentially useful for some tidal ports with (or without) navigation channels. | Keywords: | Berth allocation Column generation Container ports Port operations Tide |
Publisher: | Pergamon Press | Journal: | Transportation research. Part B, Methodological | ISSN: | 0191-2615 | EISSN: | 1879-2367 | DOI: | 10.1016/j.trb.2017.10.008 | Rights: | © 2017 Elsevier Ltd. All rights reserved. © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license https://creativecommons.org/licenses/by-nc-nd/4.0/. The following publication Zhen, L., Liang, Z., Zhuge, D., Lee, L. H., & Chew, E. P. (2017). Daily berth planning in a tidal port with channel flow control. Transportation Research Part B: Methodological, 106, 193-217 is available at https://doi.org/10.1016/j.trb.2017.10.008. |
| Appears in Collections: | Journal/Magazine Article |
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| File | Description | Size | Format | |
|---|---|---|---|---|
| Zhuge_Daily_Berth_Planning.pdf | Pre-Published version | 2.15 MB | Adobe PDF | View/Open |
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