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Parameter Analysis for Differential Evolution with Pareto Tournaments in a Multiobjective Frequency Assignment Problem

2009-09Book part Restricted access
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datacite.subject.fosCiências Naturais::Matemáticas
datacite.subject.fosCiências Naturais::Ciências da Computação e da Informação
dc.contributor.authorMaximiano, Marisa
dc.contributor.authorVega-Rodríguez, Miguel A.
dc.contributor.authorGómez-Pulido, Juan A.
dc.contributor.authorSánchez-Pérez, Juan M.
dc.date.accessioned2025-06-13T17:43:43Z
dc.date.available2025-06-13T17:43:43Z
dc.date.issued2009-09
dc.description10th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2009, 23 September 2009 through 26 September 2009 - Code 79260
dc.description.abstractThis paper presents a multiobjective approach for the Frequency Assignment Problem (FAP) in a real-world GSM network. Indeed, nowadays in GSM systems, the FAP stills continues to be a critical task for the mobile communication operators. In this work we propose a new method to address the FAP by applying the Differential Evolution (DE) algorithm in its multiobjective optimization, using the concept of Pareto Tournaments (DEPT). We present the results obtained in the tuning process of the DEPT parameters. Two distinct real-world instances of the problem - being currently operating - were tested with DEPT algorithm. Therefore, with this multiobjective approach for the FAP we are contributing to a really important applicability.eng
dc.description.sponsorshipThis work was partially funded by the Spanish Ministry of Science and Innovation and FEDER under the contract TIN2008-06491-C04-04 (the M* project). Thanks also to the Polytechnic Institute of Leiria, for the economic support offered to Marisa Maximiano to make this research.
dc.identifier.citationda Silva Maximiano, M., Vega-Rodríguez, M.A., Gómez-Pulido, J.A., Sánchez-Pérez, J.M. (2009). Parameter Analysis for Differential Evolution with Pareto Tournaments in a Multiobjective Frequency Assignment Problem. In: Corchado, E., Yin, H. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2009. IDEAL 2009. Lecture Notes in Computer Science, vol 5788. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04394-9_98.
dc.identifier.doi10.1007/978-3-642-04394-9_98
dc.identifier.eissn1611-3349
dc.identifier.isbn9783642043932
dc.identifier.isbn9783642043949EISBN
dc.identifier.issn0302-9743
dc.identifier.urihttp://hdl.handle.net/10400.8/13241
dc.language.isoeng
dc.peerreviewedyes
dc.publisherSpringer Nature
dc.relationTIN2008-06491-C04-04
dc.relation.hasversionhttps://link.springer.com/chapter/10.1007/978-3-642-04394-9_98
dc.relation.ispartofLecture Notes in Computer Science
dc.relation.ispartofIntelligent Data Engineering and Automated Learning - IDEAL 2009
dc.rights.uriN/A
dc.subjectPareto Front
dc.subjectMultiobjective Optimization
dc.subjectVariable Neighborhood Search
dc.subjectChannel Separation
dc.subjectFrequency Assignment Problem
dc.titleParameter Analysis for Differential Evolution with Pareto Tournaments in a Multiobjective Frequency Assignment Problemeng
dc.typebook part
dspace.entity.typePublication
oaire.citation.endPage806
oaire.citation.startPage799
oaire.citation.titleLecture Notes in Computer Science
oaire.citation.volume5788
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameMaximiano
person.givenNameMarisa
person.identifier.ciencia-idA919-B117-A16D
person.identifier.orcid0000-0002-1212-7864
person.identifier.scopus-author-id26767664900
relation.isAuthorOfPublication18092229-fa61-402b-978c-56b8127d46e9
relation.isAuthorOfPublication.latestForDiscovery18092229-fa61-402b-978c-56b8127d46e9

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This paper presents a multiobjective approach for the Frequency Assignment Problem (FAP) in a real-world GSM network. Indeed, nowadays in GSM systems, the FAP stills continues to be a critical task for the mobile communication operators. In this work we propose a new method to address the FAP by applying the Differential Evolution (DE) algorithm in its multiobjective optimization, using the concept of Pareto Tournaments (DEPT). We present the results obtained in the tuning process of the DEPT parameters. Two distinct real-world instances of the problem - being currently operating - were tested with DEPT algorithm. Therefore, with this multiobjective approach for the FAP we are contributing to a really important applicability.
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