Project selection is the most important problem concerning R&D management in public organizations, where weak heuristics are used for evaluating projects and making decisions about final portfolios. We propose here an integrated approach for analyzing projects and solving portfolio problems whose central parts are the use of decision tables as models of decision-maker's preferences and beliefs, and a mode! of R&D portfolio quality derived from Utility Theory and based on fuzzy sets to model some sources of imprecision. The resulting optimization problem is very complex in order to be solved by classical mathematical programming methods, so we propose an evolutionary algorithm able to achieve a strong improvement of the quality of solution. Some results are applicable in other problems outside the scope of this paper.
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