Novel decision-making approach based on grey complementary comparison preference

The weight estimation approach for uncertainty judgment matrix-interval grey numbers complementary judgment matrix in analytical hierarchy process (AHP) is studied. First, the random certainty judgment matrix of the interval numbers complementary judgment matrix is defined based on the random simulation idea. Then, the weight of the interval numbers complementary judgment matrix is expressed via the maximal value and minimal value. Moreover, the maximal weight value and minimal weight value are obtained via a simple expression. In the last, the interval weights derived from the interval numbers complementary judgment matrix are ranked to obtain the alternative order based on the possibility degree.