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Linear preselective policies for stochastic project scheduling

Author

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  • Rolf H. Möhring
  • Frederik Stork

Abstract

In the context of stochastic resource-constrained project scheduling we introduce a novel class of scheduling policies, the linear preselective policies. They combine the benefits of preselective policies and priority policies; two classes that are well known from both deterministic and stochastic scheduling. We study several properties of this new class of policies which indicate its usefulness for computational purposes. Based on a new representation of preselective policies as and/ or precedence constraints we derive efficient algorithms for computing earliest job start times and state a necessary and sufficient dominance criterion for preselective policies. A computational experiment based on 480 instances empirically validates the theoretical findings. Copyright Springer-Verlag Berlin Heidelberg 2000

Suggested Citation

  • Rolf H. Möhring & Frederik Stork, 2000. "Linear preselective policies for stochastic project scheduling," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 52(3), pages 501-515, December.
    • Handle: RePEc:spr:mathme:v:52:y:2000:i:3:p:501-515
    DOI: 10.1007/s001860000095
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    Citations

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    Cited by:

    1. Li, Haitao & Womer, Norman K., 2015. "Solving stochastic resource-constrained project scheduling problems by closed-loop approximate dynamic programming," European Journal of Operational Research, Elsevier, vol. 246(1), pages 20-33.
    2. Shoshana Hahn-Goldberg & Michael Carter & J. Beck & Maureen Trudeau & Philomena Sousa & Kathy Beattie, 2014. "Dynamic optimization of chemotherapy outpatient scheduling with uncertainty," Health Care Management Science, Springer, vol. 17(4), pages 379-392, December.
    3. Wiesemann, Wolfram & Kuhn, Daniel & Rustem, Berç, 2010. "Maximizing the net present value of a project under uncertainty," European Journal of Operational Research, Elsevier, vol. 202(2), pages 356-367, April.
    4. Gutjahr, Walter J., 2015. "Bi-Objective Multi-Mode Project Scheduling Under Risk Aversion," European Journal of Operational Research, Elsevier, vol. 246(2), pages 421-434.
    5. Roland Braune & Walter J. Gutjahr & Petra Vogl, 2022. "Stochastic radiotherapy appointment scheduling," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 30(4), pages 1239-1277, December.
    6. Masoud Arjmand & Amir Abbas Najafi & Majid Ebrahimzadeh, 2020. "Evolutionary algorithms for multi-objective stochastic resource availability cost problem," OPSEARCH, Springer;Operational Research Society of India, vol. 57(3), pages 935-985, September.

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