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Single machine scheduling with a time-dependent learning effect and deteriorating jobs

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  • J-B Wang

    (Shenyang Institute of Aeronautical Engineering)

Abstract

The paper deals with the single machine scheduling problems with a time-dependent learning effect and deteriorating jobs. By the effects of time-dependent learning and deterioration, we mean that the processing time of a job is defined by function of its starting time and total normal processing time of jobs in front of it in the sequence. It is shown that even with the introduction of a time-dependent learning effect and deteriorating jobs to job processing times, the single machine makespan minimization problem remain polynomially solvable. But for the total completion time minimization problem, the classical shortest processing time first rule or largest processing time first rule cannot give an optimal solution.

Suggested Citation

  • J-B Wang, 2009. "Single machine scheduling with a time-dependent learning effect and deteriorating jobs," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(4), pages 583-586, April.
  • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:4:d:10.1057_palgrave.jors.2602607
    DOI: 10.1057/palgrave.jors.2602607
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    References listed on IDEAS

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    1. Wen-Chiung Lee, 2004. "A Note on Deteriorating Jobs and Learning in Single-Machine Scheduling Problems," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 3(1), pages 83-89, April.
    2. Wang, Ji-Bo, 2007. "Single-machine scheduling problems with the effects of learning and deterioration," Omega, Elsevier, vol. 35(4), pages 397-402, August.
    3. Biskup, Dirk, 2008. "A state-of-the-art review on scheduling with learning effects," European Journal of Operational Research, Elsevier, vol. 188(2), pages 315-329, July.
    4. Kuo, Wen-Hung & Yang, Dar-Li, 2006. "Minimizing the total completion time in a single-machine scheduling problem with a time-dependent learning effect," European Journal of Operational Research, Elsevier, vol. 174(2), pages 1184-1190, October.
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