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Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk

Author

Listed:
  • Ali Namazian

    (Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran 1417414418, Iran)

  • Siamak Haji Yakhchali

    (Department of Industrial Engineering, College of Engineering, University of Tehran, Tehran 1417414418, Iran)

  • Vahidreza Yousefi

    (Project Management, University of Tehran, Tehran 1417414418, Iran)

  • Jolanta Tamošaitienė

    (Civil Engineering Faculty, Vilnius Gediminas Technical University, LT 2040 Vilnius, Lithuania)

Abstract

In this study, Monte Carlo simulation and Bayesian network methods are combined to present a structure for assessing the aggregated impact of risks on the completion time of a construction project. Construction projects often encounter different risks which affect and prevent their desired completion at the predicted time and budget. The probability of construction project success is increased in the case of controlling influential risks. On the other hand, interactions among risks lead to the increase of aggregated impact of risks. This fact requires paying attention to assessment and management of project aggregated risk before and during the implementation phase. The developed structure of this article considers the interactions among risks to provide an indicator for estimating the effects of risks, so that the shortage of extant models including the lack of attention to estimate the aggregated impact caused by risks and the intensifying impacts can be evaluated. Moreover, the introduced structure is implemented in an industrial case study in order to validate the model, cover the functional aspect of the problem, and explain the procedure of structure implementation in detail.

Suggested Citation

  • Ali Namazian & Siamak Haji Yakhchali & Vahidreza Yousefi & Jolanta Tamošaitienė, 2019. "Combining Monte Carlo Simulation and Bayesian Networks Methods for Assessing Completion Time of Projects under Risk," IJERPH, MDPI, vol. 16(24), pages 1-19, December.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:24:p:5024-:d:296171
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    References listed on IDEAS

    as
    1. Stefan Creemers & Erik Demeulemeester & Stijn Vonder, 2014. "A new approach for quantitative risk analysis," Annals of Operations Research, Springer, vol. 213(1), pages 27-65, February.
    2. Zhang, Limao & Wu, Xianguo & Skibniewski, Miroslaw J. & Zhong, Jingbing & Lu, Yujie, 2014. "Bayesian-network-based safety risk analysis in construction projects," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 29-39.
    3. Nordgård, D.E. & Sand, K., 2010. "Application of Bayesian networks for risk analysis of MV air insulated switch operation," Reliability Engineering and System Safety, Elsevier, vol. 95(12), pages 1358-1366.
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