Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/66028
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Building and Real Estate | - |
dc.contributor | Department of Logistics and Maritime Studies | - |
dc.creator | Qu, X | - |
dc.creator | Yi, W | - |
dc.creator | Wang, T | - |
dc.creator | Wang, S | - |
dc.creator | Xiao, L | - |
dc.creator | Liu, Z | - |
dc.date.accessioned | 2017-05-22T02:09:35Z | - |
dc.date.available | 2017-05-22T02:09:35Z | - |
dc.identifier.issn | 1058-9244 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/66028 | - |
dc.language.iso | en | en_US |
dc.publisher | Hindawi Publishing Corporation | en_US |
dc.rights | Copyright © 2017 Xiaobo Qu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | en_US |
dc.rights | The following article: Qu, X., Yi, W., Wang, T., Wang, S., Xiao, L., & Liu, Z. (2017). Mixed-integer linear programming models for teaching assistant assignment and extensions. Scientific Programming, 2017, is available at https//doi.org/10.1155/2017/9057947 | en_US |
dc.title | Mixed-integer linear programming models for teaching assistant assignment and extensions | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 2017 | en_US |
dc.identifier.doi | 10.1155/2017/9057947 | en_US |
dcterms.abstract | In this paper, we develop mixed-integer linear programming models for assigning the most appropriate teaching assistants to the tutorials in a department. The objective is to maximize the number of tutorials that are taught by the most suitable teaching assistants, accounting for the fact that different teaching assistants have different capabilities and each teaching assistant's teaching load cannot exceed a maximum value. Moreover, with optimization models, the teaching load allocation, a time-consuming process, does not need to be carried out in a manual manner. We have further presented a number of extensions that capture more practical considerations. Extensive numerical experiments show that the optimization models can be solved by an off-the-shelf solver and used by departments in universities. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Scientific programming, 2017, v. 2017, 9057947 | - |
dcterms.isPartOf | Scientific programming | - |
dcterms.issued | 2017 | - |
dc.identifier.isi | WOS:000393987500001 | - |
dc.identifier.scopus | 2-s2.0-85010299086 | - |
dc.identifier.ros | 2016003162 | - |
dc.identifier.eissn | 1875-919X | en_US |
dc.identifier.artn | 9057947 | en_US |
dc.identifier.rosgroupid | 2016003097 | - |
dc.description.ros | 2016-2017 > Academic research: refereed > Publication in refereed journal | - |
dc.description.validate | 201804_a bcma | - |
dc.description.oa | Version of Record | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
dc.description.pubStatus | Published | en_US |
dc.description.oaCategory | CC | en_US |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
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Qu_Mixed-Integer_Linear_Programming.pdf | 1.52 MB | Adobe PDF | View/Open |
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