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Risk-averse single machine scheduling: complexity and approximation

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  • Adam Kasperski

    (Wrocław University of Science and Technology)

  • Paweł Zieliński

    (Wrocław University of Science and Technology)

Abstract

In this paper, a class of single machine scheduling problems is considered. It is assumed that job processing times and due dates can be uncertain and they are specified in the form of discrete scenario set. A probability distribution in the scenario set is known. In order to choose a schedule, some risk criteria such as the value at risk and conditional value at risk are used. Various positive and negative complexity results are provided for basic single machine scheduling problems. In this paper, new complexity results are shown and some known complexity results are strengthened.

Suggested Citation

  • Adam Kasperski & Paweł Zieliński, 2019. "Risk-averse single machine scheduling: complexity and approximation," Journal of Scheduling, Springer, vol. 22(5), pages 567-580, October.
    • Handle: RePEc:spr:jsched:v:22:y:2019:i:5:d:10.1007_s10951-019-00599-6
    DOI: 10.1007/s10951-019-00599-6
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    References listed on IDEAS

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    Cited by:

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    2. Fatemeh Rezaei & Amir Abbas Najafi & Erik Demeulemeester & Reza Ramezanian, 2024. "A stochastic bi-objective project scheduling model under failure of activities," Annals of Operations Research, Springer, vol. 338(1), pages 453-476, July.

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