File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: An AIS-based hybrid algorithm with PDRs for multi-objective dynamic online job shop scheduling problem

TitleAn AIS-based hybrid algorithm with PDRs for multi-objective dynamic online job shop scheduling problem
Authors
KeywordsJob shop scheduling problem (JSSP)
Artificial immune systems (AIS)
Priority dispatching rules (PDRs)
Immune network theory
Idiotypic network
Issue Date2013
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/asoc
Citation
Applied Soft Computing, 2013, v. 13 n. 3, p. 1340-1351 How to Cite?
AbstractThe dynamic online job shop scheduling problem (JSSP) is formulated based on the classical combinatorial optimization problem – JSSP with the assumption that new jobs continuously arrive at the job shop in a stochastic manner with the existence of unpredictable disturbances during the scheduling process. This problem is hard to solve due to its inherent uncertainty and complexity. This paper models this class of problem as a multi-objective problem and solves it by hybridizing the artificial intelligence method of artificial immune systems (AIS) and priority dispatching rules (PDRs). The immune network theory of AIS is applied to establish the idiotypic network model for priority dispatching rules to dynamically control the dispatching rule selection process for each operation under the dynamic environment. Based on the defined job shop situations, the dispatching rules that perform best under specific environment conditions are selected as antibodies, which are the key elements to construct the idiotypic network. Experiments are designed to demonstrate the efficiency and competitiveness of this model.
Persistent Identifierhttp://hdl.handle.net/10722/164134
ISSN
2019 Impact Factor: 5.472
2015 SCImago Journal Rankings: 1.763
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorQiu, X-
dc.contributor.authorLau, HYK-
dc.date.accessioned2012-09-20T07:55:47Z-
dc.date.available2012-09-20T07:55:47Z-
dc.date.issued2013-
dc.identifier.citationApplied Soft Computing, 2013, v. 13 n. 3, p. 1340-1351-
dc.identifier.issn1568-4946-
dc.identifier.urihttp://hdl.handle.net/10722/164134-
dc.description.abstractThe dynamic online job shop scheduling problem (JSSP) is formulated based on the classical combinatorial optimization problem – JSSP with the assumption that new jobs continuously arrive at the job shop in a stochastic manner with the existence of unpredictable disturbances during the scheduling process. This problem is hard to solve due to its inherent uncertainty and complexity. This paper models this class of problem as a multi-objective problem and solves it by hybridizing the artificial intelligence method of artificial immune systems (AIS) and priority dispatching rules (PDRs). The immune network theory of AIS is applied to establish the idiotypic network model for priority dispatching rules to dynamically control the dispatching rule selection process for each operation under the dynamic environment. Based on the defined job shop situations, the dispatching rules that perform best under specific environment conditions are selected as antibodies, which are the key elements to construct the idiotypic network. Experiments are designed to demonstrate the efficiency and competitiveness of this model.-
dc.languageeng-
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/asoc-
dc.relation.ispartofApplied Soft Computing-
dc.subjectJob shop scheduling problem (JSSP)-
dc.subjectArtificial immune systems (AIS)-
dc.subjectPriority dispatching rules (PDRs)-
dc.subjectImmune network theory-
dc.subjectIdiotypic network-
dc.titleAn AIS-based hybrid algorithm with PDRs for multi-objective dynamic online job shop scheduling problem-
dc.typeArticle-
dc.identifier.emailLau, HYK: hyklau@hkucc.hku.hk-
dc.identifier.authorityLau, HYK=rp00137-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.asoc.2012.07.033-
dc.identifier.scopuseid_2-s2.0-84881667272-
dc.identifier.hkuros209412-
dc.identifier.volume13-
dc.identifier.issue3-
dc.identifier.spage1340-
dc.identifier.epage1351-
dc.identifier.isiWOS:000314664900003-
dc.publisher.placeNetherlands-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats