IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v337y2024i2d10.1007_s10479-022-05155-8.html
   My bibliography  Save this article

Risk response budget allocation based on fault tree analysis and optimization

Author

Listed:
  • Xin Guan

    (Jimei University)

  • Tom Servranckx

    (Ghent University)

  • Mario Vanhoucke

    (Ghent University
    Vlerick Business School
    University College London)

Abstract

Budget allocation in project risk response is a vital issue in project risk management since it relates to a reasonable utilization of strict project budgets and effective mitigations of the risks that typify projects. This paper presents an integrated method based on an optimization model and fault tree analysis for allocating a risk response budget from a preventive and protective perspective. The proposed method consists of three main steps. The first step is to analyse and calculate risk probabilities and risk losses which involves identifying risk causes that may trigger a risk event to occur using fault tree analysis. It also identifies consequences once the risk event occurs, evaluates the occurrence probabilities of risk causes and expected financial losses of consequences. The second step is to build a relationship between the budget allocated to risk response strategies and the corresponding response effects. The third step is to construct an optimization model aiming at minimizing the total risk cost. We present proofs for the optimal risk response strategy in special cases of the budget allocation model. Furthermore, a detailed computational experiment is performed to gain insights into the three-phased budget allocation model for more general cases. The results show that an optimal risk response budget can be determined and the structure of the risk network has a significant impact on the preferred risk response strategy.

Suggested Citation

  • Xin Guan & Tom Servranckx & Mario Vanhoucke, 2024. "Risk response budget allocation based on fault tree analysis and optimization," Annals of Operations Research, Springer, vol. 337(2), pages 523-564, June.
  • Handle: RePEc:spr:annopr:v:337:y:2024:i:2:d:10.1007_s10479-022-05155-8
    DOI: 10.1007/s10479-022-05155-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-05155-8
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-022-05155-8?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Akgün, İbrahim & Gümüşbuğa, Ferhat & Tansel, Barbaros, 2015. "Risk based facility location by using fault tree analysis in disaster management," Omega, Elsevier, vol. 52(C), pages 168-179.
    2. Edouard Kujawski & Diana Angelis, 2010. "Monitoring risk response actions for effective project risk management," Systems Engineering, John Wiley & Sons, vol. 13(4), pages 353-368, December.
    3. Lindu Zhao & Yiping Jiang, 2009. "A Game Theoretic Optimization Model Between Project Risk Set And Measure Set," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 8(04), pages 769-786.
    4. Martens, Annelies & Vanhoucke, Mario, 2019. "The impact of applying effort to reduce activity variability on the project time and cost performance," European Journal of Operational Research, Elsevier, vol. 277(2), pages 442-453.
    5. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2020. "The impact of a limited budget on the corrective action taking process," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1070-1086.
    6. Hanif D. Sherali & Evrim Dalkiran & Theodore S. Glickman, 2011. "Selecting Optimal Alternatives and Risk Reduction Strategies in Decision Trees," Operations Research, INFORMS, vol. 59(3), pages 631-647, June.
    7. Vanhoucke, Mario, 2010. "Using activity sensitivity and network topology information to monitor project time performance," Omega, Elsevier, vol. 38(5), pages 359-370, October.
    8. Elmaghraby, Salah E., 2005. "On the fallacy of averages in project risk management," European Journal of Operational Research, Elsevier, vol. 165(2), pages 307-313, September.
    9. I Ben-David & T Raz, 2001. "An integrated approach for risk response development in project planning," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 52(1), pages 14-25, January.
    10. Olga Špačková & Daniel Straub, 2015. "Cost‐Benefit Analysis for Optimization of Risk Protection Under Budget Constraints," Risk Analysis, John Wiley & Sons, vol. 35(5), pages 941-959, May.
    11. 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.
    12. Seyed Mohammad Seyedhoseini & Siamak Noori & Mohammad Ali Hatefi, 2009. "An Integrated Methodology for Assessment and Selection of the Project Risk Response Actions," Risk Analysis, John Wiley & Sons, vol. 29(5), pages 752-763, May.
    13. Hanif D. Sherali & Jitamitra Desai & Theodore S. Glickman, 2008. "Optimal Allocation of Risk-Reduction Resources in Event Trees," Management Science, INFORMS, vol. 54(7), pages 1313-1321, July.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zuo, Fei & Zio, Enrico & Xu, Yue, 2023. "Bi-objective optimization of the scheduling of risk-related resources for risk response," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    2. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2021. "Using Schedule Risk Analysis with resource constraints for project control," European Journal of Operational Research, Elsevier, vol. 288(3), pages 736-752.
    3. Zhang, Yao & Zuo, Fei & Guan, Xin, 2020. "Integrating case-based analysis and fuzzy optimization for selecting project risk response actions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    4. Dengsheng Wu & Xiaoqian Zhu & Jie Wan & Chunbing Bao & Jianping Li, 2019. "A Multiobjective Optimization Approach for Selecting Risk Response Strategies of Software Project: From the Perspective of Risk Correlations," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 339-364, January.
    5. Mahsa Parsaei Motamed & Shahrooz Bamdad, 2022. "A multi-objective optimization approach for selecting risk response actions: considering environmental and secondary risks," OPSEARCH, Springer;Operational Research Society of India, vol. 59(1), pages 266-303, March.
    6. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2022. "Using Earned Value Management and Schedule Risk Analysis with resource constraints for project control," European Journal of Operational Research, Elsevier, vol. 297(2), pages 451-466.
    7. 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.
    8. Song, Jie & Martens, Annelies & Vanhoucke, Mario, 2020. "The impact of a limited budget on the corrective action taking process," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1070-1086.
    9. Song, Jie & Song, Jinbo & Vanhoucke, Mario, 2025. "Automatic selection of the best performing control point approach for project control with resource constraints," European Journal of Operational Research, Elsevier, vol. 322(1), pages 15-38.
    10. 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.
    11. Mumtaz Karatas & Ertan Yakıcı & Abdullah Dasci, 2022. "Solving a bi-objective unmanned aircraft system location-allocation problem," Annals of Operations Research, Springer, vol. 319(2), pages 1631-1654, December.
    12. Ünsal Altuncan, Izel & Vanhoucke, Mario, 2025. "Duration forecasting in resource constrained projects: A hybrid risk model combining complexity indicators with sensitivity measures," European Journal of Operational Research, Elsevier, vol. 325(2), pages 329-343.
    13. Colin, Jeroen & Vanhoucke, Mario, 2014. "Setting tolerance limits for statistical project control using earned value management," Omega, Elsevier, vol. 49(C), pages 107-122.
    14. Wendi Tian & Erik Demeulemeester, 2014. "Railway scheduling reduces the expected project makespan over roadrunner scheduling in a multi-mode project scheduling environment," Annals of Operations Research, Springer, vol. 213(1), pages 271-291, February.
    15. Zhengxun Jin & Jonghyeob Kim & Chang-taek Hyun & Sangwon Han, 2019. "Development of a Model for Predicting Probabilistic Life-Cycle Cost for the Early Stage of Public-Office Construction," Sustainability, MDPI, vol. 11(14), pages 1-18, July.
    16. Xiaoyan Jiang & Sai Wang & Jie Wang & Sainan Lyu & Martin Skitmore, 2020. "A Decision Method for Construction Safety Risk Management Based on Ontology and Improved CBR: Example of a Subway Project," IJERPH, MDPI, vol. 17(11), pages 1-23, June.
    17. Pelegrín, Mercedes & Xu, Liding, 2023. "Continuous covering on networks: Improved mixed integer programming formulations," Omega, Elsevier, vol. 117(C).
    18. Meloni, Carlo & Pranzo, Marco & Samà, Marcella, 2022. "Evaluation of VaR and CVaR for the makespan in interval valued blocking job shops," International Journal of Production Economics, Elsevier, vol. 247(C).
    19. Olav Torp & Ole Jonny Klakegg, 2016. "Challenges in Cost Estimation under Uncertainty—A Case Study of the Decommissioning of Barsebäck Nuclear Power Plant," Administrative Sciences, MDPI, vol. 6(4), pages 1-21, October.
    20. Azaron, Amir & Fatemi Ghomi, S.M.T., 2008. "Lower bound for the mean project completion time in dynamic PERT networks," European Journal of Operational Research, Elsevier, vol. 186(1), pages 120-127, April.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:337:y:2024:i:2:d:10.1007_s10479-022-05155-8. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.