Title: Preference Programming for Robust Portfolio Modeling and Project Selection

Authors: Juuso Liesiö, Pekka Mild and Ahti Salo

Date: 1.4.2007

Status: European Journal of Operational Research, Vol. 181, Issue 3, pp. 1488-1505

Keywords: Multiple criteria decision analysis, project selection, portfolio optimization, incomplete information, robustness.

In decision analysis, difficulties of obtaining complete information about model parameters make it advisable to seek robust solutions that perform reasonably well across the full range of feasible parameter values. In this paper, we develop the Robust Portfolio Modeling (RPM) methodology which extends Preference Programming methods into portfolio problems where a subset of project proposals are funded in view of multiple evaluation criteria. We also develop an algorithm for computing all non-dominated portfolios, subject to incomplete information about criterion weights and project-specific performance levels. Based on these portfolios, we propose a project-level index to convey (i) which projects are robust choices (in the sense that they would be surely recommended even if further information were to be obtained) and (ii) how continued activities in preference elicitation should be focused. The RPM methodology is illustrated with an application using real data on road pavement projects.