| dc.contributor.author | Madureira, Ana Maria | |
| dc.contributor.author | Pereira, Ivo | |
| dc.date.accessioned | 2013-04-15T09:09:53Z | |
| dc.date.available | 2013-04-15T09:09:53Z | |
| dc.date.issued | 2010 | |
| dc.date.updated | 2013-04-11T18:27:45Z | |
| dc.description.abstract | Scheduling is a critical function that is present throughout many industries and applications. A great need exists for developing scheduling approaches that can be applied to a number of different scheduling problems with significant impact on performance of business organizations. A challenge is emerging in the design of scheduling support systems for manufacturing environments where dynamic adaptation and optimization become increasingly important. In this paper, we describe a Self-Optimizing Mechanism for Scheduling System through Nature Inspired Optimization Techniques (NIT). | por |
| dc.identifier.doi | 10.1007/978-90-481-9151-2_74 | pt_PT |
| dc.identifier.isbn | 978-90-481-9150-5 | |
| dc.identifier.isbn | 978-90-481-9151-2 | |
| dc.identifier.uri | http://hdl.handle.net/10400.22/1270 | |
| dc.language.iso | eng | por |
| dc.publisher | Springer Netherlands | por |
| dc.relation.ispartofseries | Technological Developments in Networking, Education and Automation; | |
| dc.relation.publisherversion | http://link.springer.com/chapter/10.1007/978-90-481-9151-2_74 | por |
| dc.subject | Self-optimization | por |
| dc.subject | Multi-agent learning | por |
| dc.subject | Autonomic computing | por |
| dc.subject | Multi-agent systems | por |
| dc.subject | Nature inspired optimization techniques | por |
| dc.title | Self-optimization for dynamic scheduling in manufacturing systems | por |
| dc.type | book part | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 426 | por |
| oaire.citation.startPage | 421 | por |
| person.familyName | Madureira | |
| person.familyName | Pereira | |
| person.givenName | Ana Maria | |
| person.givenName | Ivo | |
| person.identifier.ciencia-id | 7F1D-5AF2-A101 | |
| person.identifier.ciencia-id | 3E18-2D4C-0E14 | |
| person.identifier.orcid | 0000-0002-0264-4710 | |
| person.identifier.orcid | 0000-0001-5440-3225 | |
| person.identifier.rid | AAH-1056-2021 | |
| person.identifier.rid | N-1713-2016 | |
| person.identifier.scopus-author-id | 8634629500 | |
| person.identifier.scopus-author-id | 36675461900 | |
| rcaap.rights | closedAccess | por |
| rcaap.type | bookPart | por |
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| relation.isAuthorOfPublication | 097b47eb-e9f1-40cb-9fe3-ca46efc578cb | |
| relation.isAuthorOfPublication.latestForDiscovery | cd5e5eb7-cf63-48c6-b6b9-a9db2fedebab |
