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The trichotomic approach for dealing with uncertainty in project portfolio selection: combining MCDA, mathematical programming and Monte Carlo simulation

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  • George Mavrotas
  • Olena Pechak

Abstract

Project portfolio selection refers to the problem of selecting a certain number from a wide set of proposed projects. In this work, we also address inherent uncertainty, present either in project characteristics (e.g., costs, performances) or in decision environment (e.g., criteria weights, total budget). We model uncertainty with probability distributions and we use Monte Carlo simulation to produce MCDA parameters as well as parameters for mathematical programming model. In this way, set of projects is divided into three subsets: 'green' projects that are always present in portfolio, 'red' projects that are never selected and 'grey' projects that are selected in some of Monte Carlo runs. Subsequently, the focus is moved on grey projects for further elaboration. The so called trichotomic approach offers much more fruitful information to the decision maker as it quantifies the degree of certainty with which each project is selected or not in the final portfolio.

Suggested Citation

  • George Mavrotas & Olena Pechak, 2013. "The trichotomic approach for dealing with uncertainty in project portfolio selection: combining MCDA, mathematical programming and Monte Carlo simulation," International Journal of Multicriteria Decision Making, Inderscience Enterprises Ltd, vol. 3(1), pages 79-96.
    • Handle: RePEc:ids:ijmcdm:v:3:y:2013:i:1:p:79-96
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    Citations

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    Cited by:

    1. Panos Xidonas & Haris Doukas & George Mavrotas & Olena Pechak, 2016. "Environmental corporate responsibility for investments evaluation: an alternative multi-objective programming model," Annals of Operations Research, Springer, vol. 247(2), pages 395-413, December.
    2. George Mavrotas & Evangelos Makryvelios, 2023. "R&D project portfolio selection using the Iterative Trichotomic Approach in order to study how subjectivity of the weights is reflected in the selected projects of the final portfolio," Operational Research, Springer, vol. 23(3), pages 1-18, September.
    3. Mavrotas, George & Makryvelios, Evangelos, 2021. "Combining multiple criteria analysis, mathematical programming and Monte Carlo simulation to tackle uncertainty in Research and Development project portfolio selection: A case study from Greece," European Journal of Operational Research, Elsevier, vol. 291(2), pages 794-806.
    4. Forouli, Aikaterini & Gkonis, Nikolaos & Nikas, Alexandros & Siskos, Eleftherios & Doukas, Haris & Tourkolias, Christos, 2019. "Energy efficiency promotion in Greece in light of risk: Evaluating policies as portfolio assets," Energy, Elsevier, vol. 170(C), pages 818-831.

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