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This paper describes a three-phase approach to assist research and development managers in obtaining the most attractive project portfolio. The screening procedure of the first phase identifies project proposals that are worthy of further evaluation keeping the number of projects entering the subsequent phase within a manageable size. In the second phase, a multiobjective integer linear programming model determines the solution space of all efficient (i.e., Pareto-optimal) portfolios. It takes into account time profiles of the objectives, various project interdependencies, logical and strategic requirements, as well as resource and benefit constraints. The third phase, finally, aims to find a portfolio which fits the decision-maker's notions. Starting with an arbitrarily selected candidate he/she iteratively sets aspiration levels for objectives or modifies upper and lower bounds. Thus, the solution space is explored until a satisfying compromise between the figures both in benefit and resource categories is reached. Our approach is numerically tractable, and, as a key feature, requires no a priori assumptions about the decision-maker's preferences. Its application is illustrated by an example.