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A Consideration of Application of Attractor Selection to a Real-Time Production Scheduling

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3853))

Abstract

In this research, “attractor selection,” which adopts the concept of “attractor” chiefly defined in biological and physical fields, is applied to a scheduling problem. An attractor is an attraction area that an orbit in space converges on asymptotically, and this area denotes a stable state. The attractor to which an orbit from a certain state of an initial condition is attracted is statistically determined. Attractor selection is an algorithm that searches for a stable state flexibly under changing environments.

To apply attractor selection to a scheduling field, a scheduling framework based on scheduling strategy using a dispatching rule is introduced. A scheduling problem solution is scheduled by repeated applications of a prepared dispatching rule with plural strategies. The rule has a parameter that controls scheduling strategies based on the current “environment,” which means kinds, amounts, and remaining to due of jobs, machine conditions, etc. Attracter selection controls the parameters under changing environments.

The proposed framework was applied to a real-time production scheduling problem, and the optimality of the parameters of the strategy and followup ability were considerd when environmental changes occur.

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© 2006 Springer-Verlag Berlin Heidelberg

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Chujo, H., Oka, H., Ikkai, Y., Komoda, N. (2006). A Consideration of Application of Attractor Selection to a Real-Time Production Scheduling. In: Ijspeert, A.J., Masuzawa, T., Kusumoto, S. (eds) Biologically Inspired Approaches to Advanced Information Technology. BioADIT 2006. Lecture Notes in Computer Science, vol 3853. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11613022_29

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  • DOI: https://doi.org/10.1007/11613022_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31253-6

  • Online ISBN: 978-3-540-32438-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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