불완전한 정보하의 의사결정하에서의 아중요인 추계적-통계적 우세법칙

Multiattribute Stochastic Statistical Dominance in Decision Making with Incomplete Information

In multiattribute decision making a decision maker (DM) can choose the best alternative if his/her multiattribute utility function and the joint probability distribution of outcomes are exactly known. This paper develops multiattribute stochastic-statistical dominance rules which can be applied to the situation when neither of them is known exactly, that is, when the DM cannot calculate the expected utility for each alternative. First, the notion of relative risk aversion is used dominance rules are developed to screen out dominated alternatives so that hi/she choose the best one among the remaining nondominated alternatives.