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Minimizing total completion time on a single machine with step improving jobs

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  • Eun-Seok Kim

    (Middlesex University, London, United Kingdom)

  • Daniel Oron

    (The University of Sydney Business School, Sydney, Australia)

Abstract

Production systems often experience a shock or a technological change, resulting in performance improvement. In such settings, job processing times become shorter if jobs start processing at, or after, a common critical date. This paper considers a single machine scheduling problem with step-improving processing times, where the effects are job-dependent. The objective is to minimize the total completion time. We show that the problem is NP-hard in general and discuss several special cases which can be solved in polynomial time. We formulate a Mixed Integer Programming model and develop an LP-based heuristic for the general problem. Finally, computational experiments show that the proposed heuristic yields very effective and efficient solutions.

Suggested Citation

  • Eun-Seok Kim & Daniel Oron, 2015. "Minimizing total completion time on a single machine with step improving jobs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(9), pages 1481-1490, September.
  • Handle: RePEc:pal:jorsoc:v:66:y:2015:i:9:p:1481-1490
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