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Article: Scheduling trucks in container terminals using a genetic algorithm

TitleScheduling trucks in container terminals using a genetic algorithm
Authors
KeywordsContainer terminal
Genetic algorithm
Truck scheduling
Issue Date2007
PublisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0305215x.asp
Citation
Engineering Optimization, 2007, v. 39 n. 1, p. 33-47 How to Cite?
AbstractTrucks are the most popular transport equipment in most mega-terminals, and scheduling them to minimize makespan is a challenge that this article addresses and attempts to resolve. Specifically, the problem of scheduling a fleet of trucks to perform a set of transportation jobs with sequence-dependent processing times and different ready times is investigated, and the use of a genetic algorithm (GA) to address the scheduling problem is proposed. The scheduling problem is formulated as a mixed integer program. It is noted that the scheduling problem is NP-hard and the computational effort required to solve even small-scale test problems is prohibitively large. A crossover scheme has been developed for the proposed GA. Computational experiments are carried out to compare the performance of the proposed GA with that of GAs using six popular crossover schemes. Computational results show that the proposed GA performs best, with its solutions on average 4.05% better than the best solutions found by the other six GAs.
Persistent Identifierhttp://hdl.handle.net/10722/74255
ISSN
2015 Impact Factor: 1.38
2015 SCImago Journal Rankings: 0.866
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorNg, WCen_HK
dc.contributor.authorMak, KLen_HK
dc.contributor.authorZhang, YXen_HK
dc.date.accessioned2010-09-06T06:59:29Z-
dc.date.available2010-09-06T06:59:29Z-
dc.date.issued2007en_HK
dc.identifier.citationEngineering Optimization, 2007, v. 39 n. 1, p. 33-47en_HK
dc.identifier.issn0305-215Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/74255-
dc.description.abstractTrucks are the most popular transport equipment in most mega-terminals, and scheduling them to minimize makespan is a challenge that this article addresses and attempts to resolve. Specifically, the problem of scheduling a fleet of trucks to perform a set of transportation jobs with sequence-dependent processing times and different ready times is investigated, and the use of a genetic algorithm (GA) to address the scheduling problem is proposed. The scheduling problem is formulated as a mixed integer program. It is noted that the scheduling problem is NP-hard and the computational effort required to solve even small-scale test problems is prohibitively large. A crossover scheme has been developed for the proposed GA. Computational experiments are carried out to compare the performance of the proposed GA with that of GAs using six popular crossover schemes. Computational results show that the proposed GA performs best, with its solutions on average 4.05% better than the best solutions found by the other six GAs.en_HK
dc.languageengen_HK
dc.publisherTaylor & Francis Ltd. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/0305215x.aspen_HK
dc.relation.ispartofEngineering Optimizationen_HK
dc.subjectContainer terminalen_HK
dc.subjectGenetic algorithmen_HK
dc.subjectTruck schedulingen_HK
dc.titleScheduling trucks in container terminals using a genetic algorithmen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=0305-215X&volume=39&issue=1&spage=33&epage=47&date=2007&atitle=Scheduling+Trucks+in+Container+Terminals+Using+a+Genetic+Algorithmen_HK
dc.identifier.emailNg, WC:ngwc@hkucc.hku.hken_HK
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_HK
dc.identifier.authorityNg, WC=rp00160en_HK
dc.identifier.authorityMak, KL=rp00154en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1080/03052150600917128en_HK
dc.identifier.scopuseid_2-s2.0-33845675385en_HK
dc.identifier.hkuros129188en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33845675385&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume39en_HK
dc.identifier.issue1en_HK
dc.identifier.spage33en_HK
dc.identifier.epage47en_HK
dc.identifier.isiWOS:000242937600003-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridNg, WC=7401613494en_HK
dc.identifier.scopusauthoridMak, KL=7102680226en_HK
dc.identifier.scopusauthoridZhang, YX=7601329213en_HK
dc.identifier.citeulike1011140-

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