摘要
对区间数多指标决策问题 ,基于模糊集下论给出一种新的处理方法 :相对隶属度法 ,首先 ,构造优等与劣等方案 ,借助每一方案与优、劣等方案的综合加权距离求得每个方案相于优等方案的隶属度 ,再按隶属度的大小进行决策 ,该方法克服了以往研究此类问题时所遇到的区间数难以排序的困难。通过分析表明相对隶属度法的择优与排序能力要比传统的逼近理想解法强。最后 。
Based on fuzzy set theory, a new decision method handling multiple attribute decision-making problems with intervals is provided. It is called a relative membership degree method. The best and the worst plan are constructed, respectively. The relative membership degree to which an alternative corresponds to the best plan is obtained by means of the synthetically weighted distance between the alternative and the best and the worst plan. The decision is made by the relative membership degrees. This new method overcomes the difficulties that occur in ranking intervals in the traditional analysis methods. It is shwed that analysis that the relative membership degree method has stronger ability to choose the best and rank alternatives than the traditional TOPSIS method. An example is given.
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2004年第7期903-905,913,共4页
Systems Engineering and Electronics
基金
山东省自然科学基金资助课题 (Y2 0 0 1G0 7)
关键词
多指标决策
相对隶属度法
模糊集
区间数
multiple attribute decision-making
relative membership degree method
fuzzy set
interval