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Extraction of Priority Rules for Boolean Induction in Distributed Manufacturing Control

  • Nassima Aissani
  • Baghdad Atmani
  • Damien Trentesaux
  • Bouziane Beldjilali
Part of the Studies in Computational Intelligence book series (SCI, volume 544)

Abstract

In reactive manufacturing control, the allocation of resources for tasks is achieved in real time. When a resource becomes available it chooses one of the tasks in its queue. This choice is made according to priority rules which are designed to optimize costs, time, etc. In this paper, the aim is to exploit a Job Shop scheduling log and simulations in order to extract knowledge enabling one to create rules for the selection of priority rules. These rules are implemented in a CASI cellular automaton. Firstly, symbolic modelling of the scheduling process is exploited to generate a decision tree from the log and simulations. Secondly, decision rules are extracted to select priority rules for execution in a specific situation. Finally, the rules are integrated in CASI which implements the decisional module of agents in a distributed manufacturing control system.

Keywords

Dynamic scheduling priority rules inductive learning distributed manufacturing control 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Nassima Aissani
    • 1
  • Baghdad Atmani
    • 1
  • Damien Trentesaux
    • 2
  • Bouziane Beldjilali
    • 1
  1. 1.Laboratoire d’informatique d’Oran “LIO”, Département d’informatique, Faculté des sciencesUniversité d’OranOranAlgérie
  2. 2.Research: “Production, Services, Information” - PSI Team, TEMPO Lab. Res. Centre EA4542UVHCValenciennes cedex 9France

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