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An approach to group decision making based on interval multiplicative and fuzzy preference relations by using projection

机译:一种基于区间乘和模糊偏好关系的投影群决策方法

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This paper presents a consensus model for group decision making with interval multiplicative and fuzzy preference relations based on two consensus criteria: (1) a consensus measure which indicates the agreement between experts' preference relations and (2) a measure of proximity to find out how far the individual opinions are from the group opinion. These measures are calculated by using the relative projections of individual preference relations on the collective one, which are obtained by extending the relative projection of vectors. First, the weights of experts are determined by the relative projections of individual preference relations on the initial collective one. Then using the weights of experts, all individual preference relations are aggregated into a collective one. The consensus and proximity measures are calculated by using the relative projections of experts' preference relations respectively. The consensus measure is used to guide the consensus process until the collective solution is achieved. The proximity measure is used to guide the discussion phase of consensus reaching process. In such a way, an iterative algorithm is designed to guide the experts in the consensus reaching process. Finally the expected value preference relations are defined to transform the interval collective preference relation to a crisp one and the weights of alternatives are obtained from the expected value preference relations. Two numerical examples are given to illustrate the models and approaches.
机译:本文基于两个共识标准,提出了具有区间乘性和模糊偏好关系的群体决策的共识模型:(1)表示专家偏好关系之间一致性的共识量度;(2)找出如何进行决策的接近度量度个人意见远非集体意见。这些度量是通过使用单个偏好关系在集体关系上的相对投影来计算的,这些相对关系是通过扩展向量的相对投影而获得的。首先,专家的权重由个人偏好关系在初始集体关系上的相对投影确定。然后利用专家的权重,将所有个人偏好关系汇总为一个集体。共识度量和接近度量分别通过使用专家偏好关系的相对预测来计算。共识措施用于指导共识过程,直到实现集体解决方案为止。接近度度量值用于指导共识达成过程的讨论阶段。以这种方式,设计了一种迭代算法来指导专家达成共识。最后,定义期望值偏好关系,以将区间集体偏好关系转换为清晰的偏好关系,并从期望值偏好关系中获得替代权重。给出两个数值例子来说明模型和方法。

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