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New method of selecting efficient project portfolios in the presence of hybrid uncertainty

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  • Bogdan Rębiasz

Abstract

A new methods of selecting efficient project portfolios in the presence of hybrid uncertainty has been presented. Pareto optimal solutions have been defined by an algorithm for generating project portfolios. The method presented allows us to select efficient project portfolios taking into account statistical and economic dependencies between projects when some of the parameters used in the calculation of effectiveness can be expressed in the form of an interactive possibility distribution and some in the form of a probability distribution. The procedure for processing such hybrid data combines stochastic simulation with nonlinear programming. The interaction between data are modeled by correlation matrices and the interval regression. Economic dependences are taken into account by the equations balancing the production capacity of the company. The practical example presented indicates that an interaction between projects has a significant impact on the results of calculations.

Suggested Citation

  • Bogdan Rębiasz, 2016. "New method of selecting efficient project portfolios in the presence of hybrid uncertainty," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 26(4), pages 65-90.
    • Handle: RePEc:wut:journl:v:4:y:2016:p:65-90:id:1258
    DOI: 10.5277/ord160405
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    References listed on IDEAS

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    1. Santhanam, Radhika & Kyparisis, George J., 1996. "A decision model for interdependent information system project selection," European Journal of Operational Research, Elsevier, vol. 89(2), pages 380-399, March.
    2. Jean-Yves Jaffray & Fabrice Philippe, 1997. "On the Existence of Subjective Upper and Lower Probabilities," Mathematics of Operations Research, INFORMS, vol. 22(1), pages 165-185, February.
    3. J. Arlin Cooper & Scott Ferson & Lev Ginzburg, 1996. "Hybrid Processing of Stochastic and Subjective Uncertainty Data," Risk Analysis, John Wiley & Sons, vol. 16(6), pages 785-791, December.
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