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Integrating Neural Nets, Simulation, and Genetic Algorithms for Real-time Scheduling

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Abstract

In this paper we briefly review the generic architecture for intelligent controllers proposed in DAVIS et al. (1992). We then describe an approach for carrying out the scheduling functions contained within that architecture. This approach integrates neural networks, real-time Monte Carlo simulation, and genetic algorithms.

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© 1993 Springer-Verlag Berlin· Heidelberg

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Jones, A., Rabelo, L. (1993). Integrating Neural Nets, Simulation, and Genetic Algorithms for Real-time Scheduling. In: Fandel, G., Gulledge, T., Jones, A. (eds) Operations Research in Production Planning and Control. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-78063-9_34

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  • DOI: https://doi.org/10.1007/978-3-642-78063-9_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-78065-3

  • Online ISBN: 978-3-642-78063-9

  • eBook Packages: Springer Book Archive

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