Abstract
This paper describes a decision support system based on an additive multi‐attribute utility model for identifying the optimal strategy in complex decision‐making problems. The system allows for incomplete information on the component utility function and weight assessment, which leads to classes of utility functions and weight intervals, respectively. This makes the system suitable for group decision support, because individual conflicting views or judgements in a group of decision‐makers can be captured through imprecise responses in the respective assessment methods. Moreover, the system admits uncertainty about the multi‐attribute strategy consequences, which can be defined in term of ranges for each attribute instead of single values. The system computes non‐dominance and potential optimality to identify the most preferred strategy. We also propose an approach based on Monte Carlo simulation techniques for group decision‐making problems, which could be specially useful for e‐democracy, where several decision‐makers or groups of decision‐makers elicit their own preferences separately, which are then compared to try to reach a consensus on their respective preferences. Copyright © 2004 John Wiley & Sons, Ltd.