When selecting a portfolio (i.e., set of) projects, the projects are
often evaluated by additive scores with respect to multiple attributes.
Uncertainty or incomplete information about projects’ scores can be
modeled with plausible lower and upper bounds on the projects’ scores.
It is recommended to select a non-dominated (ND) portfolio, that is a
portfolio such that it is not possible to select another portfolio which
has (i) at least as high value with respect to every attribute for all
plausible scores, (ii) and has strictly higher value with respect to at
least one attribute for some plausible scores. In this paper, we lay a
foundation on computing (ND) project portfolios. We also present an
algorithm based on binary decision diagrams (BDDs) for generating the ND
portfolios. We show that our algorithms can provide significant
computational advantages over previous algorithms. We also explore how
BDDs can be used for storing large numbers of ND portfolios and how such
BDDs can be efficiently generated.
|Number of pages||11|
|Journal||European Journal of Operational Research|
|Publication status||Published - Jul 2017|
|MoE publication type||A1 Journal article-refereed|
- Interval uncertainty, Portfolio Decision Analysis