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

摘要

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.