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Conference Paper: A study of distributed scheduling problem with machine maintenance

TitleA study of distributed scheduling problem with machine maintenance
Authors
KeywordsDistributed scheduling
Genetic algorithm
Maintenance
Issue Date2006
PublisherBangkok, Thailand.
Citation
2006 IEEE International Conference on Cybernetics & Intelligent Systems (CIS) and Robotics, Automation & Mechatronics (RAM), p. 262-267 How to Cite?
AbstractIn this paper, we study the influence of machine maintenance to distributed scheduling problems. Distributed scheduling is aiming to maximize the system efficiency by simultaneously solving two problems: (i) allocation of jobs to suitable factories, and (ii) determination of the corresponding production scheduling in each factory. Scheduling of machine maintenance problems aim to reduce the effect of breakdown and maximize the facility availability at minimum cost. However, in many distributed scheduling problems, machine scheduling assumes that machines are available all the time. In fact, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it interrupts the production scheduling determined. This paper designed a hypothetical distributed scheduling model with three different problem sizes to demonstrate the significance of simultaneously solving machine maintenance problem with distributed scheduling problem. We applied Genetic Algorithm with Dominant Genes methodology to solve the model. Several optimization approaches, including separating and integrating the two problems, are tested and compared. The results show the merit of integration. ©2006 IEEE.
Persistent Identifierhttp://hdl.handle.net/10722/100143
References

 

DC FieldValueLanguage
dc.contributor.authorChan, FTSen_HK
dc.contributor.authorChung, SHen_HK
dc.contributor.authorChan, LYen_HK
dc.date.accessioned2010-09-25T18:58:25Z-
dc.date.available2010-09-25T18:58:25Z-
dc.date.issued2006en_HK
dc.identifier.citation2006 IEEE International Conference on Cybernetics & Intelligent Systems (CIS) and Robotics, Automation & Mechatronics (RAM), p. 262-267en_HK
dc.identifier.urihttp://hdl.handle.net/10722/100143-
dc.description.abstractIn this paper, we study the influence of machine maintenance to distributed scheduling problems. Distributed scheduling is aiming to maximize the system efficiency by simultaneously solving two problems: (i) allocation of jobs to suitable factories, and (ii) determination of the corresponding production scheduling in each factory. Scheduling of machine maintenance problems aim to reduce the effect of breakdown and maximize the facility availability at minimum cost. However, in many distributed scheduling problems, machine scheduling assumes that machines are available all the time. In fact, every machine requires maintenance, and the maintenance policy directly affects the machine's availability. Consequently, it interrupts the production scheduling determined. This paper designed a hypothetical distributed scheduling model with three different problem sizes to demonstrate the significance of simultaneously solving machine maintenance problem with distributed scheduling problem. We applied Genetic Algorithm with Dominant Genes methodology to solve the model. Several optimization approaches, including separating and integrating the two problems, are tested and compared. The results show the merit of integration. ©2006 IEEE.en_HK
dc.languageengen_HK
dc.publisherBangkok, Thailand.en_HK
dc.relation.ispartof2006 IEEE Conference on Cybernetics and Intelligent Systemsen_HK
dc.subjectDistributed schedulingen_HK
dc.subjectGenetic algorithmen_HK
dc.subjectMaintenanceen_HK
dc.titleA study of distributed scheduling problem with machine maintenanceen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailChan, FTS: ftschan@hkucc.hku.hken_HK
dc.identifier.emailChan, LY: plychan@hku.hken_HK
dc.identifier.authorityChan, FTS=rp00090en_HK
dc.identifier.authorityChan, LY=rp00093en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICCIS.2006.252261en_HK
dc.identifier.scopuseid_2-s2.0-37649030261en_HK
dc.identifier.hkuros129447en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-37649030261&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage262en_HK
dc.identifier.epage267en_HK
dc.identifier.scopusauthoridChan, FTS=7202586517en_HK
dc.identifier.scopusauthoridChung, SH=36023203100en_HK
dc.identifier.scopusauthoridChan, LY=7403540482en_HK

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