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

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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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    1. 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).
    2. 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.
    3. 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).
    4. 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.
    5. 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.
    6. 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).
    7. Seyed Farid Ghannadpour & Ali Reza Hoseini & Morteza Bagherpour & Elmira Ahmadi, 2021. "Appraising the triple bottom line utility of sustainable project portfolio selection using a novel multi-criteria house of portfolio," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(3), pages 3396-3437, March.

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