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Conference Paper: Multi-agent optimization design for multi-resource job shop scheduling problems

TitleMulti-agent optimization design for multi-resource job shop scheduling problems
Authors
Issue Date2007
Citation
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, v. 4682 LNAI, p. 1193-1204 How to Cite?
AbstractAs a practical generalization of the job shop scheduling problem, multi-resource job shop scheduling problem (MRJSSP) is discussed in this paper. In this problem, operations may be processed by a type of resources and jobs have individual deadlines. How to design and optimize this problem with DSAFO, a novel multi-agent algorithm, is introduced in detail by a case study, including problem analysis, agent role specification, and parameter selection. Experimental results show the effectiveness and efficiency of designing and optimizing MRJSSPs with multi-agent. © Springer-Verlag Berlin Heidelberg 2007.
Persistent Identifierhttp://hdl.handle.net/10722/230799
ISSN
2005 Impact Factor: 0.402
2015 SCImago Journal Rankings: 0.252

 

DC FieldValueLanguage
dc.contributor.authorXue, Fan-
dc.contributor.authorFan, Wei-
dc.date.accessioned2016-09-01T06:06:50Z-
dc.date.available2016-09-01T06:06:50Z-
dc.date.issued2007-
dc.identifier.citationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2007, v. 4682 LNAI, p. 1193-1204-
dc.identifier.issn0302-9743-
dc.identifier.urihttp://hdl.handle.net/10722/230799-
dc.description.abstractAs a practical generalization of the job shop scheduling problem, multi-resource job shop scheduling problem (MRJSSP) is discussed in this paper. In this problem, operations may be processed by a type of resources and jobs have individual deadlines. How to design and optimize this problem with DSAFO, a novel multi-agent algorithm, is introduced in detail by a case study, including problem analysis, agent role specification, and parameter selection. Experimental results show the effectiveness and efficiency of designing and optimizing MRJSSPs with multi-agent. © Springer-Verlag Berlin Heidelberg 2007.-
dc.languageeng-
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)-
dc.titleMulti-agent optimization design for multi-resource job shop scheduling problems-
dc.typeConference_Paper-
dc.description.natureLink_to_subscribed_fulltext-
dc.identifier.scopuseid_2-s2.0-38049029210-
dc.identifier.volume4682 LNAI-
dc.identifier.spage1193-
dc.identifier.epage1204-
dc.identifier.eissn1611-3349-

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