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In the research and development environment, the classical decision model, even though modified to include multiple objectives or attributes, fails in the following ways. 1) It uses linear attribute weighting functions. 2) It does not incorporate uncertainty distributions in estimates of total value and attribute attainment. 3) It does not facilitate group decision making. A computer-assisted decision model has been developed to utilize decision analysis information more effectively. A hypothetical analysis of advanced nuclear waste management alternatives illustrates its application. A simulation technique predicts the preferred decision based on estimates of attribute levels, utility functions, and an evaluation of the relative importance of the attributes.