Student Posters Repository

We introduce an integer programming formulation for ranking aggregation with ties and compare it to a modified version of a recently developed formulation. This new formulation provides computational advantages when solving large size problems. Moreover, we develop a refined social-choice related property for group decision-making, called the Generalized Condorcet Criterion, which can be regarded as a natural extension of the well-known Condorcet criterion and the Extended Condorcet criterion. Unlike its parent properties, the generalized Condorcet criterion is adequate for complete rankings with ties as well as for incomplete rankings. This property allows a simplification of solution process for very large instances of the NP-hard Kemeny ranking aggregation problem by using HPC techniques. To test the practical implications of this property, we sample complete rankings with and without ties from the Mallows statistical distribution of rank data to generate instances with differing degrees of collective cohesion.