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Efficient priority rules for the stochastic resource-constrained project scheduling problem

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  • Chen, Zhi
  • Demeulemeester, Erik
  • Bai, Sijun
  • Guo, Yuntao

Abstract

In this study we examine the performance of 17 priority rule heuristics and the justification technique on the stochastic resource-constrained project scheduling problem (SRCPSP). Among the 17 priority rules, 12 are selected from the literature that is addressing the deterministic resource-constrained project scheduling problem (RCPSP), and the other 5 are newly designed, based on stochastic information of the SRCPSP. We evaluate the efficiency of the 17 priority rules on the benchmark data set PSPLIB, and analyze the impact of the project characteristics that were used to create this data set. Our computational results on large size instances show that the best priority rule for the RCPSP does not perform best for the SRCPSP. The best priority rule for the SRCPSP performs as well as the best meta-heuristic when the variance of the activity duration is medium, and outperforms all existing algorithms when this variance is high. The validity of justification on the SRCPSP depends on the priority rule and the activity duration variance. The project characteristics network complexity and resource factor do not influence the choice of the best priority rule, but resource strength does. Our research results can aid managers to schedule project activities more efficiently when facing uncertainties.

Suggested Citation

  • Chen, Zhi & Demeulemeester, Erik & Bai, Sijun & Guo, Yuntao, 2018. "Efficient priority rules for the stochastic resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 270(3), pages 957-967.
    • Handle: RePEc:eee:ejores:v:270:y:2018:i:3:p:957-967
    DOI: 10.1016/j.ejor.2018.04.025
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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. Pejman Peykani & Jafar Gheidar-Kheljani & Sheida Shahabadi & Seyyed Hassan Ghodsypour & Mojtaba Nouri, 2023. "A two-phase resource-constrained project scheduling approach for design and development of complex product systems," Operational Research, Springer, vol. 23(1), pages 1-25, March.
    3. Bosse, Alexander & Ulmer, Marlin W. & Manni, Emanuele & Mattfeld, Dirk C., 2023. "Dynamic priority rules for combining on-demand passenger transportation and transportation of goods," European Journal of Operational Research, Elsevier, vol. 309(1), pages 399-408.
    4. Öncü Hazir & Gündüz Ulusoy, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," Post-Print hal-02898162, HAL.
    5. Osman Hürol Türkakın & David Arditi & Ekrem Manisalı, 2021. "Comparison of Heuristic Priority Rules in the Solution of the Resource-Constrained Project Scheduling Problem," Sustainability, MDPI, vol. 13(17), pages 1-17, September.
    6. Xuejun Hu & Jianjiang Wang & Kaijun Leng, 2019. "The Interaction Between Critical Chain Sequencing, Buffer Sizing, and Reactive Actions in a CC/BM Framework," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 36(03), pages 1-22, June.
    7. Zarghami, Seyed Ashkan & Dumrak, Jantanee, 2021. "Aleatory uncertainty quantification of project resources and its application to project scheduling," Reliability Engineering and System Safety, Elsevier, vol. 211(C).
    8. Hazır, Öncü & Ulusoy, Gündüz, 2020. "A classification and review of approaches and methods for modeling uncertainty in projects," International Journal of Production Economics, Elsevier, vol. 223(C).
    9. 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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