Publication
Meta-heuristics tunning using CBR for dynamic scheduling
| dc.contributor.author | Pereira, Ivo | |
| dc.contributor.author | Madureira, Ana Maria | |
| dc.date.accessioned | 2013-05-02T10:18:54Z | |
| dc.date.available | 2013-05-02T10:18:54Z | |
| dc.date.issued | 2010 | |
| dc.date.updated | 2013-04-23T11:09:47Z | |
| dc.description.abstract | This paper addresses the problem of Biological Inspired Optimization Techniques (BIT) parameterization, considering the importance of this issue in the design of BIT especially when considering real world situations, subject to external perturbations. A learning module with the objective to permit a Multi-Agent Scheduling System to automatically select a Meta-heuristic and its parameterization to use in the optimization process is proposed. For the learning process, Casebased Reasoning was used, allowing the system to learn from experience, in the resolution of similar problems. Analyzing the obtained results we conclude about the advantages of its use. | por |
| dc.identifier | DOI 10.1109/UKRICIS.2010.5898093 | |
| dc.identifier.isbn | 978-1-4244-9023-3 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/1489 | |
| dc.language.iso | eng | por |
| dc.publisher | IEEE | por |
| dc.relation.publisherversion | http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5898093 | por |
| dc.subject | Self-tuning | por |
| dc.subject | Case-based reasoning | por |
| dc.subject | Metaheuristics | por |
| dc.subject | Multi-agent system | por |
| dc.subject | Scheduling | por |
| dc.title | Meta-heuristics tunning using CBR for dynamic scheduling | por |
| dc.type | conference object | |
| dspace.entity.type | Publication | |
| oaire.citation.conferencePlace | Reading, United Kingdom, 2010 | por |
| oaire.citation.title | IEEE 9th International Conference on Cyberntic Intelligent Systems (CIS) | 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 | cd5e5eb7-cf63-48c6-b6b9-a9db2fedebab |