An efficient heuristic for adaptive production scheduling and control in one-of-a-kind production

Wei Li, Barrie R. Nault, Deyi Xue, Yiliu Tu

Research output: Contribution to journalArticlepeer-review

27 Scopus citations

Abstract

Even though research in flow shop production scheduling has been carried out for many decades, there is still a gap between research and applicationespecially in manufacturing paradigms such as one-of-a-kind production (OKP) that intensely challenges real time adaptive production scheduling and control. Indeed, many of the most popular heuristics continue to use Johnson's algorithm (1954) as their core. This paper presents a state space (SS) heuristic, integrated with a closed-loop feedback control structure, to achieve adaptive production scheduling and control in OKP. Our SS heuristic, because of its simplicity and computational efficiency, has the potential to become a core heuristic. Through a series of case studies, including an industrial implementation in OKP, our SS-based production scheduling and control system demonstrates significant potential to improve production efficiency.

Original languageEnglish
Pages (from-to)267-276
Number of pages10
JournalComputers and Operations Research
Volume38
Issue number1
DOIs
StatePublished - Jan 2011

Keywords

  • Adaptive production control
  • Flow shop scheduling
  • Petri nets
  • Simulation

ASJC Scopus subject areas

  • General Computer Science
  • Modeling and Simulation
  • Management Science and Operations Research

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