摘要
引入度量矩阵大小的lp范数来刻画关于模糊判断矩阵的相似性条件、互补性条件以及一致性条件的满足程度。通过将三个极小化问题转化为一个目的规划问题对模糊判断矩阵进行了互补一致性修正。使用控制参数λ将p=1和p=∞两类极小化偏差量的方法结合起来得到了一种更加灵活且适用范围更广的模糊判断矩阵的互补一致性修正方法。最后,用一个数值例子进行说明。
This paper introduces the l^p-norm measuring the magnitude of matrix, which represents the satisfaction degree for similarity condition, complementary condition and consistency condition of fuzzy judgment matrix. By transferring the three minimizing problems, which are corresponding to the three conditions above, into a goal programming, we improve the complementary and consistency of a fuzzy judgment matrix. Utilizing the controlling parameter λ, we integrate p=1 and p=∞ the two minimizing diversion methods and get a more flexible and more general method for improving the (complementary) and consistency of a fuzzy judgment matrix. At last, a numerical example is presented.
出处
《系统工程》
CSCD
北大核心
2005年第4期101-104,共4页
Systems Engineering
基金
国家自然科学基金资助项目(70372011)
关键词
模糊判断矩阵
相似性
互补性
一致性
目的规划
Fuzzy Judgment Matrix
Similarity
Complementary
Consistency
Goal Programming
