Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wu, MC | en_US |
dc.contributor.author | Sun, SH | en_US |
dc.date.accessioned | 2014-12-08T15:16:41Z | - |
dc.date.available | 2014-12-08T15:16:41Z | - |
dc.date.issued | 2006-05-01 | en_US |
dc.identifier.issn | 0268-3768 | en_US |
dc.identifier.uri | http://dx.doi.org/10.1007/s00170-004-2465-0 | en_US |
dc.identifier.uri | http://hdl.handle.net/11536/12303 | - |
dc.description.abstract | In a multi-project environment, we sometimes need to periodically schedule the tasks for each project and assign staff to the tasks. Such a decision-making problem has been studied in literature; however, learning effect of staff has not been considered in previous studies. This research formulates a mixed nonlinear program for project scheduling and staff allocation problems, which considers learning effect of staff. The objective function is to minimize outsourcing costs. A genetic algorithm (GA) is proposed to solve the problem. Experiments for solving various sizes of test problems has been carried out to validate the proposed GA. | en_US |
dc.language.iso | en_US | en_US |
dc.subject | genetic algorithm | en_US |
dc.subject | learning effect | en_US |
dc.subject | project scheduling | en_US |
dc.subject | staff allocation | en_US |
dc.title | A project scheduling and staff assignment model considering learning effect | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1007/s00170-004-2465-0 | en_US |
dc.identifier.journal | INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY | en_US |
dc.citation.volume | 28 | en_US |
dc.citation.issue | 11-12 | en_US |
dc.citation.spage | 1190 | en_US |
dc.citation.epage | 1195 | en_US |
dc.contributor.department | 工業工程與管理學系 | zh_TW |
dc.contributor.department | Department of Industrial Engineering and Management | en_US |
dc.identifier.wosnumber | WOS:000236974600020 | - |
dc.citation.woscount | 22 | - |
Appears in Collections: | Articles |
Files in This Item:
If it is a zip file, please download the file and unzip it, then open index.html in a browser to view the full text content.