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多属性决策问题的决策中,决策者往往对属性上的数值存在一定的心理预期。首先,通过心理预期与实际数据获得决策对象在每个属性上的满意度,对决策对象进行筛选过滤;其次,提出属性值信息相容关系,利用属性值之间的相容度进行赋权,信息融合对满足决策者心理预期的决策对象排序择优;再次,提出决策对象满意度,并指出传统的排序方法获取的最优决策对象与决策者总体满意度最大的决策对象并不等价。具体算例表明,该方法科学有效且可行。
In decision making of multi-attribute decision-making, policy makers often have some psychological expectation on the value of attribute. Firstly, we get the satisfaction degree of the decision object in each attribute through the psychological expectations and the actual data, and then filter the decision objects. Secondly, we propose the compatibility of the attribute value information, and use the compatibility between the attribute values to empower, Information fusion can make the choice of the decision-making objects to meet the expectations of the decision makers. Thirdly, the satisfaction degree of the decision-making objects is proposed. It is pointed out that the optimal decision-making objects obtained by the traditional ranking method are not equivalent to the decision-makers with the greatest overall satisfaction. Specific examples show that this method is scientifically effective and feasible.