Generation of OWA Operator Weights Based on Extreme Point Approach

In the paper, we present a general method for obtaining the OWA operator weights via extreme point approach. The extreme points are determined by the intersection of an attitudinal character constraint and a fundamental ordered weight simplex. The extreme points are completely identified by a proposed algorithm and the OWA operator weights can be expressed by a convex combination of the identified extreme points. The parameterized OWA operator weights, located in a convex hull of the identified extreme points, can then be determined specifically by appropriately selecting a parameter which is the solution of a linear (or nonlinear) mathematical program. We compare the proposed method to well-established weights generating methods including the maximum entropy, the minimal variability, and the minimax disparity approach and further we present some new OWA weights generating methods.