Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/98370
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Logistics and Maritime Studies | en_US |
| dc.creator | Zhen, L | en_US |
| dc.creator | Yu, S | en_US |
| dc.creator | Wang, S | en_US |
| dc.creator | Sun, Z | en_US |
| dc.date.accessioned | 2023-04-27T01:05:06Z | - |
| dc.date.available | 2023-04-27T01:05:06Z | - |
| dc.identifier.issn | 0254-5330 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/98370 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Springer | en_US |
| dc.rights | © Springer Science+Business Media New York 2016 | en_US |
| dc.rights | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use(https://www.springernature.com/gp/open-research/policies/accepted-manuscript-terms), but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s10479-016-2335-9. | en_US |
| dc.subject | Container port operation | en_US |
| dc.subject | OR in transportation | en_US |
| dc.subject | Quay cranes | en_US |
| dc.subject | Scheduling | en_US |
| dc.subject | Yard trucks | en_US |
| dc.title | Scheduling quay cranes and yard trucks for unloading operations in container ports | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 455 | en_US |
| dc.identifier.epage | 478 | en_US |
| dc.identifier.volume | 273 | en_US |
| dc.identifier.issue | 1-2 | en_US |
| dc.identifier.doi | 10.1007/s10479-016-2335-9 | en_US |
| dcterms.abstract | This paper studies an integrated optimization problem on quay crane and yard truck scheduling in container terminals. A mixed-integer programming model is formulated. For the model, we show the integrated scheduling problem is strongly NP-hard and investigate some properties that can considerably reduce the computational complexity. For solving the proposed model within a reasonable time, a particle swarm optimization based solution method is developed. Numerical experiments are conducted to compare the proposed method with the CPLEX solver and the genetic algorithm. The results validate the effectiveness of the proposed model and the efficiency of the proposed solution method. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Annals of operations research, 15 Feb. 2019, v. 273, no. 1-2, p. 455-478 | en_US |
| dcterms.isPartOf | Annals of operations research | en_US |
| dcterms.issued | 2019-02-15 | - |
| dc.identifier.scopus | 2-s2.0-84990866179 | - |
| dc.identifier.eissn | 1572-9338 | en_US |
| dc.description.validate | 202304 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | LMS-0471 | - |
| dc.description.fundingSource | Others | en_US |
| dc.description.fundingText | National Natural Science Foundation of China; Shanghai Social Science Research Program | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.identifier.OPUS | 6685139 | - |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Wang_Scheduling_Quay_Cranes.pdf | Pre-Published version | 1.03 MB | Adobe PDF | View/Open |
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