A method for improving the complementary and consistency conditions of fuzzy judgment matrix

This paper introduces the LP-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 goal programming, we improve the complementary and consistency conditions of a fuzzy judgment matrix. Utilizing the controlling parameter &bgr;, we integrate p=1 and p=β the two minimizing diversion methods and get a more flexible and more general method for improving the complementary and consistency conditions of a fuzzy judgment matrix. At last, a numerical example is presented.