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

  • Authors:

  • Wei Li;Barrie R. Nault;Deyi Xue;Yiliu Tu

  • Affiliations:

  • Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4;Management Information Systems Area, Haskayne School of Business, University of Calgary, Calgary, Alberta, Canada T2N 1N4;Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4;Department of Mechanical and Manufacturing Engineering, University of Calgary, Calgary, Alberta, Canada T2N 1N4

  • Venue:
  • Computers and Operations Research
  • Year:
  • 2011

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Abstract

Even though research in flow shop production scheduling has been carried out for many decades, there is still a gap between research and application-especially 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.