IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v9y2021i24p3225-d701690.html
   My bibliography  Save this article

A New Hybrid AHP and Dempster—Shafer Theory of Evidence Method for Project Risk Assessment Problem

Author

Listed:
  • Saad Muslet Albogami

    (Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Serdang, SL 43400, Malaysia)

  • Mohd Khairol Anuar Bin Mohd Ariffin

    (Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Serdang, SL 43400, Malaysia)

  • Eris Elianddy Bin Supeni

    (Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Serdang, SL 43400, Malaysia)

  • Kamarul Arifin Ahmad

    (Department of Mechanical and Manufacturing Engineering, University Putra Malaysia, Serdang, SL 43400, Malaysia)

Abstract

In this paper, a new hybrid AHP and Dempster—Shafer theory of evidence is presented for solving the problem of choosing the best project among a list of available alternatives while uncertain risk factors are taken into account. The aim is to minimize overall risks. For this purpose, a three-phase framework is proposed. In the first phase, quantitative research was conducted to identify the risk factors that can influence a project. Then, a hybrid PCA-agglomerative unsupervised machine learning algorithm is proposed to classify the projects in terms of Properties, Operational and Technological, Financial, and Strategic risk factors. In the third step, a hybrid AHP and Dempster—Shafer theory of evidence is presented to select the best alternative with the lowest level of overall risks. As a result, four groups of risk factors, including Properties, Operational and Technological, Financial, and Strategic risk factors, are considered. Afterward, using an L2^4 Taguchi method, several experiments with various dimensions have been designed which are then solved by the proposed algorithm. The outcomes are then analyzed using the Validating Index, Reduced Risk Indicator, and Solving Time. The findings indicated that, compared to classic AHP, the results of the proposed hybrid method were different in most cases due to uncertainty of risk factors. It was observed that the method could be safely used for selecting project problems in real industries.

Suggested Citation

  • Saad Muslet Albogami & Mohd Khairol Anuar Bin Mohd Ariffin & Eris Elianddy Bin Supeni & Kamarul Arifin Ahmad, 2021. "A New Hybrid AHP and Dempster—Shafer Theory of Evidence Method for Project Risk Assessment Problem," Mathematics, MDPI, vol. 9(24), pages 1-30, December.
  • Handle: RePEc:gam:jmathe:v:9:y:2021:i:24:p:3225-:d:701690
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/9/24/3225/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/9/24/3225/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Seyed Morteza Hatefi & Mohammad Ehsan Basiri & Jolanta Tamošaitienė, 2019. "An Evidential Model for Environmental Risk Assessment in Projects Using Dempster–Shafer Theory of Evidence," Sustainability, MDPI, vol. 11(22), pages 1-16, November.
    2. Xiaoyan Su & Sankaran Mahadevan & Peida Xu & Yong Deng, 2015. "Dependence Assessment in Human Reliability Analysis Using Evidence Theory and AHP," Risk Analysis, John Wiley & Sons, vol. 35(7), pages 1296-1316, July.
    3. Morteza Davari & Erik Demeulemeester, 2019. "Important classes of reactions for the proactive and reactive resource-constrained project scheduling problem," Annals of Operations Research, Springer, vol. 274(1), pages 187-210, March.
    4. Morteza Davari & Erik Demeulemeester, 2019. "The proactive and reactive resource-constrained project scheduling problem," Journal of Scheduling, Springer, vol. 22(2), pages 211-237, April.
    5. Pavol Kral & Viera Valjaskova & Katarina Janoskova, 2019. "Quantitative approach to project portfolio management: proposal for Slovak companies," Oeconomia Copernicana, Institute of Economic Research, vol. 10(4), pages 797-814, December.
    6. Chemweno, Peter & Pintelon, Liliane & Van Horenbeek, Adriaan & Muchiri, Peter, 2015. "Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 663-676.
    7. Gutjahr, Walter J., 2015. "Bi-Objective Multi-Mode Project Scheduling Under Risk Aversion," European Journal of Operational Research, Elsevier, vol. 246(2), pages 421-434.
    8. Marly Monteiro de Carvalho & Roque Rabechini Junior, 2015. "Impact of risk management on project performance: the importance of soft skills," International Journal of Production Research, Taylor & Francis Journals, vol. 53(2), pages 321-340, January.
    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. Hongbo Li & Linwen Zheng & Hanyu Zhu, 2023. "Resource leveling in projects with flexible structures," Annals of Operations Research, Springer, vol. 321(1), pages 311-342, February.
    3. Nesbitt, Peter & Blake, Lewis R. & Lamas, Patricio & Goycoolea, Marcos & Pagnoncelli, Bernardo K. & Newman, Alexandra & Brickey, Andrea, 2021. "Underground mine scheduling under uncertainty," European Journal of Operational Research, Elsevier, vol. 294(1), pages 340-352.
    4. Yutong Chen & Yongchuan Tang, 2021. "An Improved Approach of Incomplete Information Fusion and Its Application in Sensor Data-Based Fault Diagnosis," Mathematics, MDPI, vol. 9(11), pages 1-16, June.
    5. Balouka, Noemie & Cohen, Izack, 2021. "A robust optimization approach for the multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 291(2), pages 457-470.
    6. Farnaz Torabi Yeganeh & Seyed Hessameddin Zegordi, 2020. "A multi-objective optimization approach to project scheduling with resiliency criteria under uncertain activity duration," Annals of Operations Research, Springer, vol. 285(1), pages 161-196, February.
    7. Cohen, Izack & Postek, Krzysztof & Shtern, Shimrit, 2023. "An adaptive robust optimization model for parallel machine scheduling," European Journal of Operational Research, Elsevier, vol. 306(1), pages 83-104.
    8. Younes Aalian & Michel Gamache & Gilles Pesant, 2024. "Short-term underground mine planning with uncertain activity durations using constraint programming," Journal of Scheduling, Springer, vol. 27(5), pages 423-439, October.
    9. Singh, Shikha & Chandra Misra, Subhas & Kumar, Sameer, 2020. "Identification and ranking of the risk factors involved in PLM implementation," International Journal of Production Economics, Elsevier, vol. 222(C).
    10. Maziar Khoshsirat & Seyed Meysam Mousavi, 2024. "A new proactive and reactive approach for resource-constrained project scheduling problem under activity and resource disruption: a scenario-based robust optimization approach," Annals of Operations Research, Springer, vol. 338(1), pages 597-643, July.
    11. James J. H. Liou & Perry C. Y. Liu & Huai-Wei Lo, 2020. "A Failure Mode Assessment Model Based on Neutrosophic Logic for Switched-Mode Power Supply Risk Analysis," Mathematics, MDPI, vol. 8(12), pages 1-19, December.
    12. Xiong, Jian & Leus, Roel & Yang, Zhenyu & Abbass, Hussein A., 2016. "Evolutionary multi-objective resource allocation and scheduling in the Chinese navigation satellite system project," European Journal of Operational Research, Elsevier, vol. 251(2), pages 662-675.
    13. Nitin Panwar & Sanjeev Kumar, 2022. "Mathematical modelling and performance analysis of screening unit in paper plant," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 13(5), pages 2751-2763, October.
    14. Silvia Martínez-Perales & Isabel Ortiz-Marcos & Jesús Juan Ruiz & Francisco Javier Lázaro, 2018. "Using Certification as a Tool to Develop Sustainability in Project Management," Sustainability, MDPI, vol. 10(5), pages 1-18, May.
    15. Paraskevopoulos, Dimitris C. & Laporte, Gilbert & Repoussis, Panagiotis P. & Tarantilis, Christos D., 2017. "Resource constrained routing and scheduling: Review and research prospects," European Journal of Operational Research, Elsevier, vol. 263(3), pages 737-754.
    16. Seyed Morteza Hatefi & Hanieh Ahmadi & Jolanta Tamošaitienė, 2025. "Risk Assessment in Mass Housing Projects Using the Integrated Method of Fuzzy Shannon Entropy and Fuzzy EDAS," Sustainability, MDPI, vol. 17(2), pages 1-20, January.
    17. Jamaliah Said & Md. Mahmudul Alam & Razana Juhaida Johari, 2020. "Assessment of risk management practices in the public sector of Malaysia," International Journal of Business and Emerging Markets, Inderscience Enterprises Ltd, vol. 12(4), pages 377-390.
    18. Rong Yuan & Debiao Meng & Haiqing Li, 2016. "Multidisciplinary reliability design optimization using an enhanced saddlepoint approximation in the framework of sequential optimization and reliability analysis," Journal of Risk and Reliability, , vol. 230(6), pages 570-578, December.
    19. Shengwen Yin & Keliang Jin & Yu Bai & Wei Zhou & Zhonggang Wang, 2023. "Solution-Space-Reduction-Based Evidence Theory Method for Stiffness Evaluation of Air Springs with Epistemic Uncertainty," Mathematics, MDPI, vol. 11(5), pages 1-19, March.
    20. Gholamreza Dehdasht & Rosli Mohamad Zin & M. Salim Ferwati & Mu’azu Mohammed Abdullahi & Ali Keyvanfar & Ronald McCaffer, 2017. "DEMATEL-ANP Risk Assessment in Oil and Gas Construction Projects," Sustainability, MDPI, vol. 9(8), pages 1-24, August.

    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:gam:jmathe:v:9:y:2021:i:24:p:3225-:d:701690. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.