A fuzzy-neural slack-diversifying rule for job dispatching in a wafer fabrication factory - a simulation study

Tin-Chih Chen*, Michelle Huang

*Corresponding author for this work

Research output: Contribution to journalArticle

Abstract

This study proposes a fuzzy-neural slack-diversifying nonlinear fluctuation smoothing (NFS) rule to improve the performance of job dispatching in a wafer fabrication factory. The fuzzy-neural slack-diversifying NFS rule is derived from the one-factor tailored nonlinear fluctuation smoothing rule for mean cycle time (1f-TNFSMCT) by dynamically maximizing the standard deviation of the slack, which has been shown to improve scheduling performance in several previous studies. According to the experimental results, the proposed methodology outperformed some existing approaches.

Original languageEnglish
Pages (from-to)2243-2247
Number of pages5
JournalICIC Express Letters
Volume6
Issue number9
StatePublished - 17 Sep 2012

Keywords

  • Dispatching rule
  • Diversify
  • Fluctuation smoothing
  • Slack
  • Wafer fabrication

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