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A Hybrid Differential Evolution Algorithm for Solving the Terminal Assignment Problem
datacite.subject.fos | Ciências Naturais::Matemáticas | |
datacite.subject.fos | Ciências Naturais::Ciências da Computação e da Informação | |
dc.contributor.author | Bernardino, Eugénia | |
dc.contributor.author | Bernardino, Anabela | |
dc.contributor.author | Sánchez-Pérez, Juan Manuel | |
dc.contributor.author | Gómez-Pulido, Juan Antonio | |
dc.contributor.author | Vega-Rodríguez, Miguel Angel | |
dc.date.accessioned | 2025-06-03T10:55:31Z | |
dc.date.available | 2025-06-03T10:55:31Z | |
dc.date.issued | 2009-06 | |
dc.description | 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, 10 June 2009 through 12 June 2009 - Code 77015 | |
dc.description.abstract | The field of communication networks has witnessed tremendous growth in recent years resulting in a large variety of combinatorial optimization problems in the design and in the management of communication networks. One of these problems is the terminal assignment problem. The task here is to assign a given set of terminals to a given set of concentrators. In this paper, we propose a Hybrid Differential Evolution Algorithm to solve the terminal assignment problem. We compare our results with the results obtained by the classical Genetic Algorithm and the Tabu Search Algorithm, widely used in literature. | eng |
dc.identifier.citation | Bernardino, E.M., Bernardino, A.M., Sánchez-Pérez, J.M., Gómez-Pulido, J.A., Vega-Rodríguez, M.A. (2009). A Hybrid Differential Evolution Algorithm for Solving the Terminal Assignment Problem. In: Omatu, S., et al. Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living. IWANN 2009. Lecture Notes in Computer Science, vol 5518. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02481-8_25. | |
dc.identifier.doi | 10.1007/978-3-642-02481-8_25 | |
dc.identifier.eissn | 1611-3349 | |
dc.identifier.isbn | 9783642024801 | |
dc.identifier.isbn | 9783642024818 | |
dc.identifier.issn | 0302-9743 | |
dc.identifier.uri | http://hdl.handle.net/10400.8/13075 | |
dc.language.iso | eng | |
dc.peerreviewed | yes | |
dc.publisher | Springer Nature | |
dc.relation.hasversion | https://link.springer.com/chapter/10.1007/978-3-642-02481-8_25 | |
dc.relation.ispartof | Lecture Notes in Computer Science | |
dc.relation.ispartof | Distributed Computing, Artificial Intelligence, Bioinformatics, Soft Computing, and Ambient Assisted Living | |
dc.rights.uri | N/A | |
dc.subject | Communication Networks | |
dc.subject | Genetic Algorithms | |
dc.subject | Hybrid Differential Evolution Algorithm | |
dc.subject | Tabu Search | |
dc.subject | Terminal Assignment Problem | |
dc.title | A Hybrid Differential Evolution Algorithm for Solving the Terminal Assignment Problem | eng |
dc.type | book part | |
dspace.entity.type | Publication | |
oaire.citation.endPage | 186 | |
oaire.citation.issue | PART II | |
oaire.citation.startPage | 179 | |
oaire.citation.title | Lecture Notes in Computer Science | |
oaire.citation.volume | 5518 | |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
person.familyName | Bernardino | |
person.familyName | Moreira Bernardino | |
person.givenName | Eugénia | |
person.givenName | Anabela | |
person.identifier.ciencia-id | 9616-F1BC-D8BD | |
person.identifier.ciencia-id | 081E-F3B8-316A | |
person.identifier.orcid | 0000-0001-5301-5853 | |
person.identifier.orcid | 0000-0002-6561-5730 | |
person.identifier.scopus-author-id | 24402754700 | |
relation.isAuthorOfPublication | 893cf15c-eff8-4e43-949c-c1de6eb87599 | |
relation.isAuthorOfPublication | 375ebe15-f84c-46a4-a3d9-6e4935a92187 | |
relation.isAuthorOfPublication.latestForDiscovery | 893cf15c-eff8-4e43-949c-c1de6eb87599 |
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- The field of communication networks has witnessed tremendous growth in recent years resulting in a large variety of combinatorial optimization problems in the design and in the management of communication networks. One of these problems is the terminal assignment problem. The task here is to assign a given set of terminals to a given set of concentrators. In this paper, we propose a Hybrid Differential Evolution Algorithm to solve the terminal assignment problem. We compare our results with the results obtained by the classical Genetic Algorithm and the Tabu Search Algorithm, widely used in literature.
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