Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98260
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Logistics and Maritime Studies | en_US |
| dc.creator | Zhen, L | en_US |
| dc.creator | Sun, Q | en_US |
| dc.creator | Zhang, W | en_US |
| dc.creator | Wang, K | en_US |
| dc.creator | Yi, W | en_US |
| dc.date.accessioned | 2023-04-27T01:04:20Z | - |
| dc.date.available | 2023-04-27T01:04:20Z | - |
| dc.identifier.issn | 0160-5682 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/98260 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Palgrave Macmillan | en_US |
| dc.rights | © Operational Research Society 2020 | en_US |
| dc.rights | 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. | en_US |
| dc.subject | Berth allocation | en_US |
| dc.subject | Carbon taxation | en_US |
| dc.subject | Column generation | en_US |
| dc.subject | Green port | en_US |
| dc.subject | Quay crane assignment | en_US |
| dc.subject | Uncertainty | en_US |
| dc.title | Column generation for low carbon berth allocation under uncertainty | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 2225 | en_US |
| dc.identifier.epage | 2240 | en_US |
| dc.identifier.volume | 72 | en_US |
| dc.identifier.issue | 10 | en_US |
| dc.identifier.doi | 10.1080/01605682.2020.1776168 | en_US |
| dcterms.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. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Journal of the Operational Research Society, 2021, v. 72, no. 10, p. 2225-2240 | en_US |
| dcterms.isPartOf | Journal of the Operational Research Society | en_US |
| dcterms.issued | 2021 | - |
| dc.identifier.scopus | 2-s2.0-85091609947 | - |
| dc.identifier.eissn | 1476-9360 | en_US |
| dc.description.validate | 202304 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | LMS-0150 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | National Natural Science Foundation of China; National Key R&D Program of China | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 55189488 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| 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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