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Adjustable robustness for multi-attribute project portfolio selection

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  • Fliedner, Thomas
  • Liesiö, Juuso

Abstract

Robust Portfolio Modeling (RPM) supports multi-attribute project portfolio selection with uncertain project scores and decision maker preferences. By determining non-dominated portfolios for all possible realizations of uncertain parameters, decision recommendations produced by RPM may prove too conservative for real-life decision problems. We develop a methodology to reduce the set of possible realizations by limiting the number of project scores that may simultaneously deviate from their most likely value. By adjusting this limit, decision makers can choose desired levels of conservatism. Our approach also allows to capture dependencies among project scores as well as uncertainty in portfolio constraints.

Suggested Citation

  • Fliedner, Thomas & Liesiö, Juuso, 2016. "Adjustable robustness for multi-attribute project portfolio selection," European Journal of Operational Research, Elsevier, vol. 252(3), pages 931-946.
    • Handle: RePEc:eee:ejores:v:252:y:2016:i:3:p:931-946
    DOI: 10.1016/j.ejor.2016.01.058
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    Cited by:

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    15. Marques, Adriana Cavalcante & Frej, Eduarda Asfora & de Almeida, Adiel Teixeira, 2022. "Multicriteria decision support for project portfolio selection with the FITradeoff method," Omega, Elsevier, vol. 111(C).
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    19. Seunghoon Lee & Young Hoon Lee & Yongho Choi, 2019. "Project Portfolio Selection Considering Total Cost of Ownership in the Automobile Industry," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    20. Ran Etgar & Yuval Cohen, 2022. "Roadmap Optimization: Multi-Annual Project Portfolio Selection Method," Mathematics, MDPI, vol. 10(9), pages 1-23, May.
    21. Sameer Bathallath & Åsa Smedberg & Harald Kjellin, 2019. "The Viable System Model for Diagnosing and Handling IT-Project Interdependencies in Large Portfolios," International Journal of Information Technology Project Management (IJITPM), IGI Global, vol. 10(1), pages 72-87, January.
    22. Santos, Maria João & Curcio, Eduardo & Mulati, Mauro Henrique & Amorim, Pedro & Miyazawa, Flávio Keidi, 2020. "A robust optimization approach for the vehicle routing problem with selective backhauls," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 136(C).
    23. Liesiö, Juuso & Salo, Ahti & Keisler, Jeffrey M. & Morton, Alec, 2021. "Portfolio decision analysis: Recent developments and future prospects," European Journal of Operational Research, Elsevier, vol. 293(3), pages 811-825.

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