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Conference Paper: A lagrangian based immune-inspired optimization framework for distributed systems

TitleA lagrangian based immune-inspired optimization framework for distributed systems
Authors
KeywordsArtificial immune systems (AIS)
Conflicts resolution
Distributed systems
Lagrangian decomposition
Issue Date2008
PublisherIEEE.
Citation
Conference Proceedings - Ieee International Conference On Systems, Man And Cybernetics, 2008, p. 1326-1331 How to Cite?
AbstractThis paper presents a novel hybrid framework for cooperative conflict resolution in distributed system (DS) optimization problems that combines the Lagrangian decomposition (LD) method and the mechanisms offered by artificial immune systems. LD provides a means to derive simpler sub-problems by dropping complicated constraints, yet the challenge is to determine effective algorithms for updating the corresponding multipliers. After full decomposition of a single optimization problem derived from a DS into a number of sub-problems that are to be solved by individual intelligent agents, this paper introduces a distributed cooperative search framework (DCSF) whereby intelligent agents are designed for solving those sub-problems. The development of DCSF is inspired by the human immune system where algorithms of suppression and stimulation are formulated to compute the infeasibility (violation of relaxation constraints) and the affinity of candidate solutions individually. In this paper, DCSF is implemented on a distributed platform supported by Matlab to solve a generalized assignment problem (GAP) so as to demonstrate its behavior and performance in the realm of distributed combinatorial optimization. © 2008 IEEE.
DescriptionIEEE International Conference on System Man and Cybernetics (SMC 2008)
Persistent Identifierhttp://hdl.handle.net/10722/62174
ISSN
References

 

DC FieldValueLanguage
dc.contributor.authorLau, HYKen_HK
dc.contributor.authorLu, SYPen_HK
dc.date.accessioned2010-07-13T03:55:29Z-
dc.date.available2010-07-13T03:55:29Z-
dc.date.issued2008en_HK
dc.identifier.citationConference Proceedings - Ieee International Conference On Systems, Man And Cybernetics, 2008, p. 1326-1331en_HK
dc.identifier.issn1062-922Xen_HK
dc.identifier.urihttp://hdl.handle.net/10722/62174-
dc.descriptionIEEE International Conference on System Man and Cybernetics (SMC 2008)en_HK
dc.description.abstractThis paper presents a novel hybrid framework for cooperative conflict resolution in distributed system (DS) optimization problems that combines the Lagrangian decomposition (LD) method and the mechanisms offered by artificial immune systems. LD provides a means to derive simpler sub-problems by dropping complicated constraints, yet the challenge is to determine effective algorithms for updating the corresponding multipliers. After full decomposition of a single optimization problem derived from a DS into a number of sub-problems that are to be solved by individual intelligent agents, this paper introduces a distributed cooperative search framework (DCSF) whereby intelligent agents are designed for solving those sub-problems. The development of DCSF is inspired by the human immune system where algorithms of suppression and stimulation are formulated to compute the infeasibility (violation of relaxation constraints) and the affinity of candidate solutions individually. In this paper, DCSF is implemented on a distributed platform supported by Matlab to solve a generalized assignment problem (GAP) so as to demonstrate its behavior and performance in the realm of distributed combinatorial optimization. © 2008 IEEE.en_HK
dc.languageengen_HK
dc.publisherIEEE.en_HK
dc.relation.ispartofConference Proceedings - IEEE International Conference on Systems, Man and Cyberneticsen_HK
dc.rights©2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.en_HK
dc.subjectArtificial immune systems (AIS)en_HK
dc.subjectConflicts resolutionen_HK
dc.subjectDistributed systemsen_HK
dc.subjectLagrangian decompositionen_HK
dc.titleA lagrangian based immune-inspired optimization framework for distributed systemsen_HK
dc.typeConference_Paperen_HK
dc.identifier.emailLau, HYK:hyklau@hkucc.hku.hken_HK
dc.identifier.authorityLau, HYK=rp00137en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/ICSMC.2008.4811469en_HK
dc.identifier.scopuseid_2-s2.0-69949148037en_HK
dc.identifier.hkuros143753en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-69949148037&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.spage1326en_HK
dc.identifier.epage1331en_HK
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridLau, HYK=7201497761en_HK
dc.identifier.scopusauthoridLu, SYP=55017179600en_HK

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