Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98260
| Title: | Column generation for low carbon berth allocation under uncertainty | Authors: | Zhen, L Sun, Q Zhang, W Wang, K Yi, W |
Issue Date: | 2021 | Source: | Journal of the Operational Research Society, 2021, v. 72, no. 10, p. 2225-2240 | Abstract: | This article investigates a low carbon-oriented berth allocation and quay crane assignment problem considering vessels’ uncertain arrival time and loading/unloading workload for vessels. A two-stage stochastic programming model is formulated based on a set of scenarios. The first stage designs a baseline schedule and the second stage adjusts the schedule in each scenario. A solution method is developed by using column generation techniques. Numerical experiments are conducted to validate the efficiency of our column generation-based solution method and the effectiveness of the proposed decision model. Some sensitivity analysis is also performed to draw some managerial implications. | Keywords: | Berth allocation Carbon taxation Column generation Green port Quay crane assignment Uncertainty |
Publisher: | Palgrave Macmillan | Journal: | Journal of the Operational Research Society | ISSN: | 0160-5682 | EISSN: | 1476-9360 | DOI: | 10.1080/01605682.2020.1776168 | Rights: | © Operational Research Society 2020 This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of the Operational Research Society on 25 Sep 2020 (published online), available at: http://www.tandfonline.com/10.1080/01605682.2020.1776168. |
| Appears in Collections: | Journal/Magazine Article |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Zhang_Column_Generation_Low.pdf | Pre-Published version | 1.19 MB | Adobe PDF | View/Open |
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