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dc.contributor.author박장현-
dc.date.accessioned2017-08-03T04:57:29Z-
dc.date.available2017-08-03T04:57:29Z-
dc.date.issued2015-10-
dc.identifier.citationProc. of The Third Intl. Conf. on Advances in Mechanical and Robotics Engineering - AMRE 2015 , Page. 26-27en_US
dc.identifier.isbn978-1-63248-066-8-
dc.identifier.urihttps://pdfs.semanticscholar.org/0a6b/bbc4f6ad105bbd47df8ca363d657d8c44357.pdf-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/28245-
dc.description.abstractIn this paper, we present and solve a scheduling problem for a high-density robotic workcell under various working conditions. The genetic algorithm (GA) is employed to optimize tasks for scheduling of the multi-robot system. A new operation method for generating subsequent generations of GA, controlled mutation is introduced depending on the value of the objective function in order to help the algorithm get out of the local minimum. Several simulation graphs verify efficiency of the proposed algorithm.en_US
dc.language.isoenen_US
dc.publisherIREDen_US
dc.subjectMulti-objective genetic algorithmen_US
dc.subjectHigh-density roboten_US
dc.subjectSchedulingen_US
dc.subjectMTSPen_US
dc.titleTask Scheduling for a Multi-Robot System using Genetic Algorithmen_US
dc.typeArticleen_US
dc.relation.page26-27-
dc.contributor.googleauthorPark, Jahng Hyon-
dc.contributor.googleauthorJeong, Jinhan-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF AUTOMOTIVE ENGINEERING-
dc.identifier.pidjpark-
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COLLEGE OF ENGINEERING[S](공과대학) > AUTOMOTIVE ENGINEERING(미래자동차공학과) > Articles
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