Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.22/1465
Título: Self-optimizing through CBR learning
Autor: Pereira, Ivo
Madureira, Ana Maria
Palavras-chave: Scheduling
Data: 2010
Editora: IEEE
Resumo: 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.
URI: http://hdl.handle.net/10400.22/1465
ISBN: 978-1-4244-6909-3
Versão do Editor: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5586081
Aparece nas colecções:ISEP – GECAD – Comunicações em eventos científicos

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