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Publicação
Self-optimizing through CBR learning
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| 1.23 MB | Adobe PDF |
Orientador(es)
Resumo(s)
In this paper, we foresee the use of Multi-Agent
Systems for supporting dynamic and distributed scheduling in
Manufacturing Systems. We also envisage the use of Autonomic
properties in order to reduce the complexity of managing
systems and human interference. By combining Multi-Agent
Systems, Autonomic Computing, and Nature Inspired
Techniques we propose an approach for the resolution of
dynamic scheduling problem, with Case-based Reasoning
Learning capabilities. The objective is to permit a system to be
able to automatically adopt/select a Meta-heuristic and
respective parameterization considering scheduling
characteristics. From the comparison of the obtained results
with previous results, we conclude about the benefits of its use.
Descrição
Palavras-chave
Scheduling
Contexto Educativo
Citação
Editora
IEEE