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Utilising the chaos-induced discrete self organising migrating algorithm to solve the lot-streaming flowshop scheduling problem with setup time

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dc.title Utilising the chaos-induced discrete self organising migrating algorithm to solve the lot-streaming flowshop scheduling problem with setup time en
dc.contributor.author Davendra, Donald David
dc.contributor.author Šenkeřík, Roman
dc.contributor.author Zelinka, Ivan
dc.contributor.author Pluháček, Michal
dc.contributor.author Bialic-Davendra, Magdalena Lucyna
dc.relation.ispartof Soft Computing
dc.identifier.issn 1432-7643 Scopus Sources, Sherpa/RoMEO, JCR
dc.identifier.issn 1433-7479 Scopus Sources, Sherpa/RoMEO, JCR
dc.date.issued 2014
utb.relation.volume 18
utb.relation.issue 4
dc.citation.spage 669
dc.citation.epage 681
dc.type article
dc.language.iso en
dc.publisher Springer-Verlag Berlin
dc.identifier.doi 10.1007/s00500-014-1219-7
dc.relation.uri https://link.springer.com/article/10.1007/s00500-014-1219-7
dc.subject Delayed Logistic map en
dc.subject Discrete Self Organising Migrating algorithm en
dc.subject Lot-streaming flowshop scheduling en
dc.subject Lozi map en
dc.description.abstract The Dissipative Lozi chaotic map is embedded in the discrete self organising migrating algorithm (DSOMA), as a pseudorandom generator. This novel chaotic based algorithm is applied to the constraint based lot-streaming flowshop scheduling problem. Two new and unique data sets generated using the Lozi and Delayed Logistic maps are used to compare the chaos embedded DSOMA and the generic DSOMA utilising the venerable Mersenne Twister. In total, 100 data sets were tested by these two algorithms, for the idling and the non-idling case. From the obtained results, the chaos variant algorithm is shown to significantly improve the performance of generic DSOMA. © 2014 Springer-Verlag Berlin Heidelberg. en
utb.faculty Faculty of Applied Informatics
dc.identifier.uri http://hdl.handle.net/10563/1003715
utb.identifier.obdid 43871777
utb.identifier.scopus 2-s2.0-84897580695
utb.identifier.wok 000333030800006
utb.source j-scopus
dc.date.accessioned 2014-05-07T13:49:22Z
dc.date.available 2014-05-07T13:49:22Z
utb.contributor.internalauthor Šenkeřík, Roman
utb.contributor.internalauthor Pluháček, Michal
utb.contributor.internalauthor Bialic-Davendra, Magdalena Lucyna
utb.fulltext.affiliation Donald Davendra · Roman Senkerik · Ivan Zelinka · Michal Pluhacek · Magdalena Bialic-Davendra Communicated by I. Zelinka. D. Davendra (B) · I. Zelinka Department of Computing Science, Faculty of Electrical Engineering and Computer Science, VSB-Technical University of Ostrava, 17. listopadu 15, 708 33 Ostrava-Poruba, Czech Republic e-mail: donald.davendra@vsb.cz I. Zelinka e-mail: ivan.zelinka@vsb.cz R. Senkerik · M. Pluhacek Department of Informatics and Artificial Intelligence, Faculty of Applied Informatics, Tomas Bata University in Zlin, Nad Stranemi 4511, 760 05 Zlin, Czech Republic e-mail: senkerik@fai.utb.cz M. Pluhacek e-mail: pluhacek@fai.utb.cz M. Bialic-Davendra Centre for Applied Economic Research, Faculty of Management and Economics, Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01 Zlin, Czech Republic e-mail: bialic@fame.utb.cz
utb.fulltext.dates Published online: 30 January 2014
utb.fulltext.sponsorship Donald Davendra was supported by the Technology Agency of the Czech Republic under the Project TE01020197 and Michal Pluhacek was supported by the Internal Grant Agency of Tomas Bata University under the project No. IGA/FAI/2013/012.
utb.fulltext.faculty Faculty of Applied Informatics
utb.fulltext.faculty Faculty of Management and Economics
utb.fulltext.ou Department of Informatics and Artificial Intelligence
utb.fulltext.ou Centre for Applied Economic Research
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