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A project scheduling and staff assignment model considering learning effect

dc.citation.epage1195en_US
dc.citation.issue11-12en_US
dc.citation.spage1190en_US
dc.citation.volume28en_US
dc.citation.woscount22
dc.contributor.authorWu, MCen_US
dc.contributor.authorSun, SHen_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.date.accessioned2014-12-08T15:16:41Z
dc.date.available2014-12-08T15:16:41Z
dc.date.issued2006-05-01en_US
dc.description.abstractIn 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.identifier.doi10.1007/s00170-004-2465-0en_US
dc.identifier.issn0268-3768en_US
dc.identifier.journalINTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGYen_US
dc.identifier.urihttp://dx.doi.org/10.1007/s00170-004-2465-0en_US
dc.identifier.urihttps://ir.lib.nycu.edu.tw/handle/11536/12303
dc.identifier.wosnumberWOS:000236974600020
dc.language.isoen_USen_US
dc.subjectgenetic algorithmen_US
dc.subjectlearning effecten_US
dc.subjectproject schedulingen_US
dc.subjectstaff allocationen_US
dc.titleA project scheduling and staff assignment model considering learning effecten_US
dc.typeArticleen_US

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