Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/6719
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | - |
dc.creator | Xue, F | - |
dc.creator | Chan, CY | - |
dc.creator | Ip, WH | - |
dc.creator | Cheung, CF | - |
dc.date.accessioned | 2014-12-11T08:22:59Z | - |
dc.date.available | 2014-12-11T08:22:59Z | - |
dc.identifier.uri | http://hdl.handle.net/10397/6719 | - |
dc.language.iso | en | en_US |
dc.rights | Posted with permission of the author. | en_US |
dc.title | Towards a learning-based heuristic searching reform scheme | en_US |
dc.type | Presentation | en_US |
dcterms.abstract | The authors investigate the issue of improving heuristic searching with supervised learning in large scale optimization. | - |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | Paper presented at the 24th European Conference on Operational Research (EURO XXIV), Lisbon, Portugal, 11-14 July 2010 | - |
dcterms.issued | 2010-07 | - |
dc.description.oa | Other Version | en_US |
dc.identifier.FolderNumber | OA_IR/PIRA | en_US |
Appears in Collections: | Presentation |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
EUROXXIV.pdf | 2.78 MB | Adobe PDF | View/Open |
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