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A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process

Author

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  • Tavana, Madjid
  • Khosrojerdi, Ghasem
  • Mina, Hassan
  • Rahman, Amirah

Abstract

The primary goal in project portfolio management is to select and manage the optimal set of projects that contribute the maximum in business value. However, selecting Information Technology (IT) projects is a difficult task due to the complexities and uncertainties inherent in the strategic-operational nature of the process, and the existence of both quantitative and qualitative criteria. We propose a two-stage process to select an optimal project portfolio with the aim of maximizing project benefits and minimizing project risks. We construct a two-stage hybrid mathematical programming model by integrating Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Inference System (FIS). This hybrid framework provides the ability to consider both the quantitative and qualitative criteria while considering budget constraints and project risks. We also present a real-world case study in the cybersecurity industry to exhibit the applicability and demonstrate the efficacy of our proposed method.

Suggested Citation

  • Tavana, Madjid & Khosrojerdi, Ghasem & Mina, Hassan & Rahman, Amirah, 2019. "A hybrid mathematical programming model for optimal project portfolio selection using fuzzy inference system and analytic hierarchy process," Evaluation and Program Planning, Elsevier, vol. 77(C).
    • Handle: RePEc:eee:epplan:v:77:y:2019:i:c:s0149718919301922
    DOI: 10.1016/j.evalprogplan.2019.101703
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    References listed on IDEAS

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    7. Wu, Huang & Shen, Jianping & Jones, Jeffrey & Gao, Xingyuan & Zheng, Yunzheng & Krenn, Huilan Y., 2019. "Using logic model and visualization to conduct portfolio evaluation," Evaluation and Program Planning, Elsevier, vol. 74(C), pages 69-75.
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    2. Tian, Yuanyuan & Bai, Libiao & Wei, Lan & Zheng, Kanyin & Zhou, Xinyu, 2022. "Modeling for project portfolio benefit prediction via a GA-BP neural network," Technological Forecasting and Social Change, Elsevier, vol. 183(C).
    3. Attari, Mahdi Yousfi Nejad & Moslemi Beirami, Ali Asghar & Ala, Ali & Jami, Ensiye Neyshabouri, 2023. "Resolving the practical factors in the healthcare system management by considering a combine approach of AHP and ANP methods," Evaluation and Program Planning, Elsevier, vol. 100(C).
    4. M. Kandakoglu & G. Walther & S. Ben Amor, 2024. "The use of multi-criteria decision-making methods in project portfolio selection: a literature review and future research directions," Annals of Operations Research, Springer, vol. 332(1), pages 807-830, January.
    5. Nitidetch Koohathongsumrit & Pongchanun Luangpaiboon, 2022. "An integrated FAHP–ZODP approach for strategic marketing information system project selection," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 43(6), pages 1792-1809, September.
    6. Govindan, Kannan & Mina, Hassan & Alavi, Behrouz, 2020. "A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 138(C).
    7. Fatemeh Parvaneh & Ahmed Hammad, 2024. "Application of Multi-Criteria Decision-Making (MCDM) to Select the Most Sustainable Power-Generating Technology," Sustainability, MDPI, vol. 16(8), pages 1-32, April.
    8. Hannan Amoozad Mahdiraji & Aliasghar Abbasi Kamardi & Moein Beheshti & Seyed Hossein Razavi Hajiagha & Luis Rocha-Lona, 2022. "Analysing supply chain coordination mechanisms dealing with repurposing challenges during Covid-19 pandemic in an emerging economy: a multi-layer decision making approach," Operations Management Research, Springer, vol. 15(3), pages 1341-1360, December.
    9. Masoud Rahiminezhad Galankashi & Farimah Mokhatab Rafiei & Maryam Ghezelbash, 2020. "Portfolio selection: a fuzzy-ANP approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-34, December.

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