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Conference Paper: An AIS-based hybrid algorithm with PSO for Job Shop Scheduling Problem

TitleAn AIS-based hybrid algorithm with PSO for Job Shop Scheduling Problem
Authors
KeywordsArtificial Immune Systems (AIS)
Clonal Selection
Immune Network
Job Shop Scheduling Problem (JSSP)
Particle Swarm Optimization (PSO)
Issue Date2010
Citation
The 10th IFAC Workshop on Intelligent Manufacturing Systems (IMS'10), Lisbon, Portugal, 1-2 July 2010. In IFAC Proceedings Volumes, 2010, pt. 1, p. 350-355 How to Cite?
AbstractJob Shop Scheduling Problem (JSSP) is a traditional NP-hard combinational optimization problem. In this paper, we propose a new hybrid method based on Artificial Immune Systems (AIS) and Particle Swarm Optimization (PSO) to solve JSSP with an objective of minimizing the makespan while satisfying the predefined constraints. Two AIS theories, namely, clonal selection theory and immune network theory are adopted. The former establishes the fundamental processes including selection, cloning, hypermutation and receptor editing, and the latter increases the diversity for the potential solution set. For the random hypermutation process, PSO is applied to optimize and accelerate the search process. This algorithm is tested on 20 benchmark problems with four different sizes. The results shows that its performance is encouraging, especially for small size problems.
Persistent Identifierhttp://hdl.handle.net/10722/158843
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorQiu, Xen_US
dc.contributor.authorLau, HYKen_US
dc.date.accessioned2012-08-08T09:03:34Z-
dc.date.available2012-08-08T09:03:34Z-
dc.date.issued2010en_US
dc.identifier.citationThe 10th IFAC Workshop on Intelligent Manufacturing Systems (IMS'10), Lisbon, Portugal, 1-2 July 2010. In IFAC Proceedings Volumes, 2010, pt. 1, p. 350-355en_US
dc.identifier.issn1474-6670en_US
dc.identifier.urihttp://hdl.handle.net/10722/158843-
dc.description.abstractJob Shop Scheduling Problem (JSSP) is a traditional NP-hard combinational optimization problem. In this paper, we propose a new hybrid method based on Artificial Immune Systems (AIS) and Particle Swarm Optimization (PSO) to solve JSSP with an objective of minimizing the makespan while satisfying the predefined constraints. Two AIS theories, namely, clonal selection theory and immune network theory are adopted. The former establishes the fundamental processes including selection, cloning, hypermutation and receptor editing, and the latter increases the diversity for the potential solution set. For the random hypermutation process, PSO is applied to optimize and accelerate the search process. This algorithm is tested on 20 benchmark problems with four different sizes. The results shows that its performance is encouraging, especially for small size problems.en_US
dc.languageengen_US
dc.relation.ispartofIFAC Proceedings Volumes (IFAC-Papers Online)en_US
dc.subjectArtificial Immune Systems (AIS)en_US
dc.subjectClonal Selectionen_US
dc.subjectImmune Networken_US
dc.subjectJob Shop Scheduling Problem (JSSP)en_US
dc.subjectParticle Swarm Optimization (PSO)en_US
dc.titleAn AIS-based hybrid algorithm with PSO for Job Shop Scheduling Problemen_US
dc.typeConference_Paperen_US
dc.identifier.emailLau, HYK: hyklau@hkucc.hku.hken_US
dc.identifier.authorityLau, HYK=rp00137en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.scopuseid_2-s2.0-80051970932en_US
dc.identifier.hkuros180474-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-80051970932&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume10en_US
dc.identifier.issuept. 1en_US
dc.identifier.spage350en_US
dc.identifier.epage355en_US
dc.identifier.scopusauthoridQiu, X=48361881900en_US
dc.identifier.scopusauthoridLau, HYK=7201497761en_US
dc.customcontrol.immutablesml 160106 - merged-

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