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Compu-search methodologies II: Scheduling using genetic algorithms and artificial neural networks

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Book cover The Planning and Scheduling of Production Systems

Abstract

This chapter complements the previous chapter ‘Scheduling Methodology: Optimization and Compu-search Approaches I’ about the scheduling level of a production manufacturing hierarchical approach. It presents various ways of using genetic algorithms and artificial neural networks to solve scheduling problems. Genetic algorithms are used for scheduling problems without assignment unknown values (solutions are completely decribed by the list of job sequences on each resource). The potential use of artificial neural networks for solving scheduling problems is illustrated with a simple multiprocessor scheduling problem.

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Authors
  1. F. Alexandre
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  2. C. Cardeira
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  3. F. Charpillet
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  4. Z. Mammeri
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  5. M.-C. Portmann
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Editor information

Editors and Affiliations

  1. FUCAM University, 151 Chaussee de Binche, B7000, Mons, Belgium

    A. Artiba (Professor of Industrial Management and Computer Science) (Professor of Industrial Management and Computer Science)

  2. Graduate Program in Operations Research, North Carolina State University, Box 7913, Raleigh, NC, 27695-7913, USA

    S. E. Elmaghraby (University Professor of Operations Research and Industrial Engineering) (University Professor of Operations Research and Industrial Engineering)

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© 1997 Chapman & Hall

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Alexandre, F., Cardeira, C., Charpillet, F., Mammeri, Z., Portmann, MC. (1997). Compu-search methodologies II: Scheduling using genetic algorithms and artificial neural networks. In: Artiba, A., Elmaghraby, S.E. (eds) The Planning and Scheduling of Production Systems. Springer, Boston, MA. https://doi.org/10.1007/978-1-4613-1195-9_10

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  • DOI: https://doi.org/10.1007/978-1-4613-1195-9_10

  • Publisher Name: Springer, Boston, MA

  • Print ISBN: 978-1-4612-8507-6

  • Online ISBN: 978-1-4613-1195-9

  • eBook Packages: Springer Book Archive

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