Publication
Multi-apprentice learning for meta-heuristics parameter tuning in a multi agent scheduling system
| dc.contributor.author | Pereira, Ivo | |
| dc.contributor.author | Madureira, Ana Maria | |
| dc.contributor.author | Moura, Paulo Oliveira | |
| dc.date.accessioned | 2013-05-13T11:41:23Z | |
| dc.date.available | 2013-05-13T11:41:23Z | |
| dc.date.issued | 2012 | |
| dc.date.updated | 2013-04-23T11:03:12Z | |
| dc.description.abstract | The scheduling problem is considered in complexity theory as a NP-hard combinatorial optimization problem. Meta-heuristics proved to be very useful in the resolution of this class of problems. However, these techniques require parameter tuning which is a very hard task to perform. A Case-based Reasoning module is proposed in order to solve the parameter tuning problem in a Multi-Agent Scheduling System. A computational study is performed in order to evaluate the proposed CBR module performance. | por |
| dc.identifier | DOI 10.1109/NaBIC.2012.6402236 | |
| dc.identifier.isbn | 978-1-4673-4767-9 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/1556 | |
| dc.language.iso | eng | por |
| dc.publisher | IEEE | por |
| dc.relation.publisherversion | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6402236 | por |
| dc.subject | Case-based reasoning | por |
| dc.subject | Learning | por |
| dc.subject | Meta-heuristics | por |
| dc.subject | Parameter tuning | por |
| dc.subject | Scheduling | por |
| dc.title | Multi-apprentice learning for meta-heuristics parameter tuning in a multi agent scheduling system | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Mexico City, Mexico, 2012 | por |
| oaire.citation.endPage | 35 | por |
| oaire.citation.startPage | 31 | por |
| oaire.citation.title | Fourth World Congress on Nature and Biologically Inspired Computing (NaBIC) | por |
| person.familyName | Pereira | |
| person.familyName | Madureira | |
| person.givenName | Ivo | |
| person.givenName | Ana Maria | |
| person.identifier.ciencia-id | 3E18-2D4C-0E14 | |
| person.identifier.ciencia-id | 7F1D-5AF2-A101 | |
| person.identifier.orcid | 0000-0001-5440-3225 | |
| person.identifier.orcid | 0000-0002-0264-4710 | |
| person.identifier.rid | N-1713-2016 | |
| person.identifier.rid | AAH-1056-2021 | |
| person.identifier.scopus-author-id | 36675461900 | |
| person.identifier.scopus-author-id | 8634629500 | |
| rcaap.rights | closedAccess | por |
| rcaap.type | conferenceObject | por |
| relation.isAuthorOfPublication | 097b47eb-e9f1-40cb-9fe3-ca46efc578cb | |
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| relation.isAuthorOfPublication.latestForDiscovery | 097b47eb-e9f1-40cb-9fe3-ca46efc578cb |