On optimization models for aggregating incomplete preferences

We consider the methods for aggregating preferences that ate based on the resolution of discrete optimization problems. The preferences are represented by an array of arbitrary incomplete paired comparison matrices. This incomplete case remains practically unexplored so far. We examine the properties of several known methods and propose one new method. In particular, we test whether these methods satisfy a new condition referred here as Self-Consistent Monotonicity.