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A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects

Author

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  • Georgios K. Koulinas

    (Department of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias St., 67100 Xanthi, Greece)

  • Olympia E. Demesouka

    (Department of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias St., 67100 Xanthi, Greece)

  • Konstantinos A. Sidas

    (Department of Engineering Project Management, Faculty of Science & Technology, Hellenic Open University, Parodos Aristotelous 18 St., 26335 Patra, Greece)

  • Dimitrios E. Koulouriotis

    (Department of Production and Management Engineering, Democritus University of Thrace, 12 Vas. Sofias St., 67100 Xanthi, Greece)

Abstract

In this paper, we propose a process that combines the Risk Matrix approach with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and the Monte Carlo Simulation for assessing risk factors that have an impact on the duration of a construction project’s activities and predict if it is feasible to terminate the project within the prescribed deadlines. Initially, we identified the risks affecting each task of the specific project, and then, we applied the risk matrix approach for determining the probability and impact of every risk to each activity. The resulting ranking is used to assign uncertainty to activities’ durations and estimate the probability of on-time project completion, employing the Monte Carlo Simulation approach. The main contribution of this paper is the development of an innovative framework that coordinates an established qualitative and quantitative risk classification approach, with a popular multicriteria method and a powerful simulation approach, to effectively predict time deviations while executing complex construction projects under uncertainty. The proposed framework was applied to estimate the possibility of a timely execution of an artificial lake real project on the island of Alonissos, Greece. The analysis results illustrate that this approach clearly could help the project risk manager proactively perform risk mitigation measures while allocating budget and programming a project with a significant impact on the quality of life of residents and tourists of a small island.

Suggested Citation

  • Georgios K. Koulinas & Olympia E. Demesouka & Konstantinos A. Sidas & Dimitrios E. Koulouriotis, 2021. "A TOPSIS—Risk Matrix and Monte Carlo Expert System for Risk Assessment in Engineering Projects," Sustainability, MDPI, vol. 13(20), pages 1-14, October.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:20:p:11277-:d:654968
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    References listed on IDEAS

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    Cited by:

    1. Frantisek Kuda & Petr Dlask & Marek Teichmann & Vaclav Beran, 2022. "Time–Cost Schedules and Project–Threats Indication," Sustainability, MDPI, vol. 14(5), pages 1-16, February.
    2. F. Acebes & J. M. González-Varona & A. López-Paredes & J. Pajares, 2024. "Beyond probability-impact matrices in project risk management: A quantitative methodology for risk prioritisation," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
    3. Andrea Senova & Alica Tobisova & Robert Rozenberg, 2023. "New Approaches to Project Risk Assessment Utilizing the Monte Carlo Method," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    4. Jianwang Wang & Lan Luo & Rina Sa & Wei Zhou & Zihan Yu, 2023. "A Quantitative Analysis of Decision-Making Risk Factors for Mega Infrastructure Projects in China," Sustainability, MDPI, vol. 15(21), pages 1-25, October.

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