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Bounding the Project Completion Time Distribution in PERT Networks

Author

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  • Bajis Dodin

    (University of California, Riverside, California)

Abstract

We consider the PERT model of a project composed of activities whose durations are random variables with known distributions. For the situations in which the activity durations are completely independent, we present a new method for obtaining a probability distribution function that bounds the exact probability distribution of the project completion time from below. The bounding distribution can be used to obtain an upper bound on the mean completion time of the project. We also prove and illustrate that this bounding distribution is better (tighter) than any of the existing lower bounds, implying that the corresponding upper bound on the mean completion time is tighter than any of the existing upper bounds.

Suggested Citation

  • Bajis Dodin, 1985. "Bounding the Project Completion Time Distribution in PERT Networks," Operations Research, INFORMS, vol. 33(4), pages 862-881, August.
    • Handle: RePEc:inm:oropre:v:33:y:1985:i:4:p:862-881
    DOI: 10.1287/opre.33.4.862
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    Cited by:

    1. Williams, Terry, 1999. "Towards realism in network simulation," Omega, Elsevier, vol. 27(3), pages 305-314, June.
    2. Yakhchali, Siamak Haji & Ghodsypour, Seyed Hassan, 2010. "Computing latest starting times of activities in interval-valued networks with minimal time lags," European Journal of Operational Research, Elsevier, vol. 200(3), pages 874-880, February.
    3. Guanglin Xu & Samuel Burer, 2018. "A data-driven distributionally robust bound on the expected optimal value of uncertain mixed 0-1 linear programming," Computational Management Science, Springer, vol. 15(1), pages 111-134, January.
    4. Hajdu M. & Isaac S., 2016. "Sixty years of project planning: history and future," Organization, Technology and Management in Construction, Sciendo, vol. 8(1), pages 1499-1510, December.
    5. Williams, Terry, 1995. "A classified bibliography of recent research relating to project risk management," European Journal of Operational Research, Elsevier, vol. 85(1), pages 18-38, August.
    6. Zhichao Zheng & Karthik Natarajan & Chung-Piaw Teo, 2016. "Least Squares Approximation to the Distribution of Project Completion Times with Gaussian Uncertainty," Operations Research, INFORMS, vol. 64(6), pages 1406-1421, December.
    7. Dubois, Didier & Fargier, Helene & Galvagnon, Vincent, 2003. "On latest starting times and floats in activity networks with ill-known durations," European Journal of Operational Research, Elsevier, vol. 147(2), pages 266-280, June.
    8. Banerjee, Arunava & Paul, Anand, 2008. "On path correlation and PERT bias," European Journal of Operational Research, Elsevier, vol. 189(3), pages 1208-1216, September.
    9. Vaseghi, Forough & Martens, Annelies & Vanhoucke, Mario, 2024. "Analysis of the impact of corrective actions for stochastic project networks," European Journal of Operational Research, Elsevier, vol. 316(2), pages 503-518.
    10. Schmidt, Craig W. & Grossmann, Ignacio E., 2000. "The exact overall time distribution of a project with uncertain task durations," European Journal of Operational Research, Elsevier, vol. 126(3), pages 614-636, November.
    11. Davaadorjin Monhor, 2011. "A new probabilistic approach to the path criticality in stochastic PERT," 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. 19(4), pages 615-633, December.
    12. Li, Xiaobo & Natarajan, Karthik & Teo, Chung-Piaw & Zheng, Zhichao, 2014. "Distributionally robust mixed integer linear programs: Persistency models with applications," European Journal of Operational Research, Elsevier, vol. 233(3), pages 459-473.
    13. Brucker, Peter & Drexl, Andreas & Mohring, Rolf & Neumann, Klaus & Pesch, Erwin, 1999. "Resource-constrained project scheduling: Notation, classification, models, and methods," European Journal of Operational Research, Elsevier, vol. 112(1), pages 3-41, January.
    14. Van de Vonder, Stijn & Demeulemeester, Erik & Herroelen, Willy & Leus, Roel, 2005. "The use of buffers in project management: The trade-off between stability and makespan," International Journal of Production Economics, Elsevier, vol. 97(2), pages 227-240, August.
    15. Badinelli, Ralph D., 1996. "Approximating probability density functions and their convolutions using orthogonal polynomials," European Journal of Operational Research, Elsevier, vol. 95(1), pages 211-230, November.
    16. Javier Castro & Daniel Gómez & Juan Tejada, 2014. "Allocating slacks in stochastic PERT network," 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. 22(1), pages 37-52, March.
    17. Lee, Heejung & Suh, Hyo-Won, 2008. "Estimating the duration of stochastic workflow for product development process," International Journal of Production Economics, Elsevier, vol. 111(1), pages 105-117, January.
    18. Tetsuo Iida, 2000. "Computing bounds on project duration distributions for stochastic PERT networks," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(7), pages 559-580, October.
    19. Huang, Ding-Hsiang & Huang, Cheng-Fu & Lin, Yi-Kuei, 2020. "Exact project reliability for a multi-state project network subject to time and budget constraints," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    20. Xuan Vinh Doan & Karthik Natarajan, 2012. "On the Complexity of Nonoverlapping Multivariate Marginal Bounds for Probabilistic Combinatorial Optimization Problems," Operations Research, INFORMS, vol. 60(1), pages 138-149, February.

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