Scheduling in flexible manufacturing systems (FMS) must take into account the shorter lead time, the multiprocessing environment, and the dynamically changing states. In this paper, a pattern-directed approach is presented which incorporates a nonlinear planning method developed in the artificial intelligence field. The scheduling system described here is knowledge-based and utilizes both forward-and backward-chaining for generating schedules (treated as state-space plans). The pattern-directed approach is dynamically adjustable and thus can handle scheduling requirements unique to the FMS environment, such as dynamic scheduling, failure-recovery scheduling, or prioritized scheduling for meeting deadlines.

Original languageEnglish (US)
Pages (from-to)353-376
Number of pages24
JournalAnnals of Operations Research
Issue number1
StatePublished - Dec 1988


  • Artificial intelligence
  • FMS scheduling
  • heuristic search
  • pattern-directed inference

ASJC Scopus subject areas

  • General Decision Sciences
  • Management Science and Operations Research


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