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Article: Scheduling yard cranes in a container terminal using a new genetic approach

TitleScheduling yard cranes in a container terminal using a new genetic approach
Authors
KeywordsGenetic Algorithm
Hybrid Algorithm
Inter-Crane Interference
Tabu Search
Yard Crane
Issue Date2009
PublisherInternational Association of Engineers. The Journal's web site is located at http://www.engineeringletters.com/
Citation
Engineering Letters, 2009, v. 17 n. 4 How to Cite?
AbstractEffective and efficient scheduling of yard crane operations is essential to guarantee a smooth and fast container flow in a container terminal, thus leading to a high terminal throughput. This paper studies the problem of scheduling yard cranes to perform a given set of loading and unloading jobs with different ready times in a yard zone. In particular, the inter-crane interference between adjacent yard cranes which results in the movement of a yard crane being blocked by adjacent yard cranes is studied. The objective is to minimize the sum of yard crane completing times. Since the scheduling problem is NP-complete, a new hybrid optimization algorithm combining the techniques of genetic algorithm and tabu search method (GA-TS) is proposed to solve the challenging problem. Two new operators, namely the Tabu Search Crossover (TSC) and the Tabu Search Mutation (TSM), are introduced into the proposed algorithm to ensure efficient computation. A set of test problems generated randomly based on real life data is used to evaluate the performance of the proposed algorithm. Computational results clearly indicate that GA-TS can successfully locate cost-effective solutions which are on average 20% better than that located by GA. Indeed, the proposed hybrid algorithm is an effective and efficient means for scheduling yard cranes in computer terminals.
Persistent Identifierhttp://hdl.handle.net/10722/155923
ISSN
2015 SCImago Journal Rankings: 0.241
References

 

DC FieldValueLanguage
dc.contributor.authorMak, KLen_US
dc.contributor.authorSun, Den_US
dc.date.accessioned2012-08-08T08:38:26Z-
dc.date.available2012-08-08T08:38:26Z-
dc.date.issued2009en_US
dc.identifier.citationEngineering Letters, 2009, v. 17 n. 4en_US
dc.identifier.issn1816-093Xen_US
dc.identifier.urihttp://hdl.handle.net/10722/155923-
dc.description.abstractEffective and efficient scheduling of yard crane operations is essential to guarantee a smooth and fast container flow in a container terminal, thus leading to a high terminal throughput. This paper studies the problem of scheduling yard cranes to perform a given set of loading and unloading jobs with different ready times in a yard zone. In particular, the inter-crane interference between adjacent yard cranes which results in the movement of a yard crane being blocked by adjacent yard cranes is studied. The objective is to minimize the sum of yard crane completing times. Since the scheduling problem is NP-complete, a new hybrid optimization algorithm combining the techniques of genetic algorithm and tabu search method (GA-TS) is proposed to solve the challenging problem. Two new operators, namely the Tabu Search Crossover (TSC) and the Tabu Search Mutation (TSM), are introduced into the proposed algorithm to ensure efficient computation. A set of test problems generated randomly based on real life data is used to evaluate the performance of the proposed algorithm. Computational results clearly indicate that GA-TS can successfully locate cost-effective solutions which are on average 20% better than that located by GA. Indeed, the proposed hybrid algorithm is an effective and efficient means for scheduling yard cranes in computer terminals.en_US
dc.languageengen_US
dc.publisherInternational Association of Engineers. The Journal's web site is located at http://www.engineeringletters.com/en_US
dc.relation.ispartofEngineering Lettersen_US
dc.subjectGenetic Algorithmen_US
dc.subjectHybrid Algorithmen_US
dc.subjectInter-Crane Interferenceen_US
dc.subjectTabu Searchen_US
dc.subjectYard Craneen_US
dc.titleScheduling yard cranes in a container terminal using a new genetic approachen_US
dc.typeArticleen_US
dc.identifier.emailMak, KL:makkl@hkucc.hku.hken_US
dc.identifier.authorityMak, KL=rp00154en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-71649096412en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-71649096412&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume17en_US
dc.identifier.issue4en_US
dc.publisher.placeHong Kongen_US
dc.identifier.scopusauthoridMak, KL=7102680226en_US
dc.identifier.scopusauthoridSun, D=35213981700en_US

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