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Parallel machine scheduling with general sum of processing time based models

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  • Radosław Rudek

    (Wrocław University of Economics)

Abstract

In this paper, we analyse the parallel machine makespan minimization problem with the general sum of processing time based learning or aging effects. First, we prove that an optimal solution to the single machine case can be found by priority rules. Next, for the considered parallel machine problem, we construct the exact dynamic programming algorithm that can operate on real-valued job processing times, which is the only exact algorithm for the analysed problem. The computational analysis confirms that it can solve optimally moderate problem instances.

Suggested Citation

  • Radosław Rudek, 2017. "Parallel machine scheduling with general sum of processing time based models," Journal of Global Optimization, Springer, vol. 68(4), pages 799-814, August.
    • Handle: RePEc:spr:jglopt:v:68:y:2017:i:4:d:10.1007_s10898-017-0509-x
    DOI: 10.1007/s10898-017-0509-x
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    References listed on IDEAS

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    Cited by:

    1. Annear, Luis Mauricio & Akhavan-Tabatabaei, Raha & Schmid, Verena, 2023. "Dynamic assignment of a multi-skilled workforce in job shops: An approximate dynamic programming approach," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1109-1125.
    2. Derya Deliktaş, 2022. "Self-adaptive memetic algorithms for multi-objective single machine learning-effect scheduling problems with release times," Flexible Services and Manufacturing Journal, Springer, vol. 34(3), pages 748-784, September.

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