PROBE multicriteria decision support system for portfolio robustness evaluation. This paper addresses the problem of selecting a robust portfolio of projects in the context of limited resources, multiple criteria, different project interactions and several types of uncertainty. A portfolio of projects is considered an undoubtedly robust choice if for a given uncertainty domain that affects the costs and/or the benefits of the projects there is no other portfolio that does not cost more and simultaneously may provide more overall benefit. We present a new decision support system, PROBE (Portfolio Robustness Evaluation), and the algorithms it implements. PROBE identifies all efficient portfolios and depicts the respective Pareto frontier within a given portfolio cost range, and permits users to analyze, in depth, the robustness of selecting a proposed portfolio. The robustness evaluation starts by identifying competitor portfolios to the proposed portfolio, its similarities and differences in project composition to its competitors, and the regret a decision-maker may have by selecting the proposed portfolio instead of a competitor.

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  1. Frej, Eduarda Asfora; Ekel, Petr; de Almeida, Adiel Teixeira: A benefit-to-cost ratio based approach for portfolio selection under multiple criteria with incomplete preference information (2021)
  2. Jin, Xiaowan; Ji, Ying; Qu, Shaojian: Minimum cost strategic weight assignment for multiple attribute decision-making problem using robust optimization approach (2021)
  3. Liesiö, Juuso; Salo, Ahti; Keisler, Jeffrey M.; Morton, Alec: Portfolio decision analysis: recent developments and future prospects (2021)
  4. Liesiö, Juuso; Vilkkumaa, Eeva: Nonadditive multiattribute utility functions for portfolio decision analysis (2021)
  5. Liesiö, Juuso; Andelmin, Juho; Salo, Ahti: Efficient allocation of resources to a portfolio of decision making units (2020)
  6. Harju, Mikko; Liesiö, Juuso; Virtanen, Kai: Spatial multi-attribute decision analysis: axiomatic foundations and incomplete preference information (2019)
  7. Tervonen, Tommi; Liesiö, Juuso; Salo, Ahti: Modeling project preferences in multiattribute portfolio decision analysis (2017)
  8. Fliedner, Thomas; Liesiö, Juuso: Adjustable robustness for multi-attribute project portfolio selection (2016)
  9. Greco, Salvatore (ed.); Ehrgott, Matthias (ed.); Figueira, José Rui (ed.): Multiple criteria decision analysis. State of the art surveys. In 2 volumes (2016)
  10. Pereira, Javier; Crawford, Broderick; Paredes, Fernando; Soto, Ricardo: A bicriteria approach identifying nondominated portfolios (2014)
  11. Bana e Costa, Carlos A.; Carnero, María Carmen; Oliveira, Mónica Duarte: A multi-criteria model for auditing a predictive maintenance programme (2012)