| Multiple attribute decision making is an important part of modern decision theory. It has been widely used in economy and management. However, many problems in economy and management are soft, where the rage of decision problem is fuzzy or some attributes can hardly be expressed in normal way. Thus, the research is transforming from traditional multi-attribute decision making to fuzzy multi-attribute decision making. Therefore, this research is meaningful. In this thesis, several problems of interval numbers fuzzy multiple attribute decision making have been studied.(1) A research of ranking interval numbers. Firstly, the concept of relative satisfaction degree is defined, and the way of determining target interval numbers is proposed. Secondly, the data of the distance between each interval numbers and the target interval numbers, and the relative satisfaction degree of each interval numbers to the target interval numbers are picked up. Thirdly, a new ranking method is proposed by comparing the similar of each interval numbers to the target interval numbers in the collected data. Finally, by considering the different preference of each decision maker to the middle and the wild of interval numbers, a similarity degree of considering decision makers’ preference is defined and a ranking method of considering decision makers’ preference is proposed.(2) A research of deriving interval weights from an additive consistent interval fuzzy preference relation. Firstly, according to the relationship of elements in fuzzy preference relation, a kind of additive consistent information transforming way is determined. Secondly, this additive consistent information transforming way is extended to the interval environment. Then, a kind of additive consistent information transforming way in additive consistent interval fuzzy preference relation is determined. And all additive consistent information in additive consistent interval fuzzy preference relation is collected. Thirdly, interval weights are generated by the relationships between additive consistent information and the weights.(3) A research of deriving interval weights from a multiplicative consistent interval fuzzy preference relation. Firstly, according to the relationships between additive consistent fuzzy preference relation and consistent reciprocal preference relation, and the relationships between multiplicative consistent fuzzy preference relation and consistent reciprocal preference relation, relationships between additive consistent fuzzy preference relation and multiplicative consistent fuzzy preference relation are established. Secondly, the relationships are extended to the interval environment and relationships between additive consistent interval fuzzy preference relation and multiplicative consistent interval fuzzy preference relation are established. Thirdly, by the transforming relationships, a multiplicative consistent interval fuzzy preference relation is transformed into an additive consistent interval fuzzy preference relation to collect the additive consistent information. Finally, the collected additive consistent information is transformed into multiplicative consistent information to derive interval weights. |
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