Mathematical programming formulations for the efficient solution of the k-sum approval voting problem

In this paper we address the problem of electing a committee among a set of m candidates on the basis of the preferences of a set of n voters. We consider the approval voting method in which each voter can approve as many candidates as he likes by expressing a preference profile (boolean m-vector). In order to elect a committee, a voting rule must be established to 'transform' the n voters' profiles into a winning committee. The problem is widely studied in voting theory; for a variety of voting rules the problem was shown to be computationally difficult and approximation algorithms and heuristic techniques were proposed in the literature. In this paper we follow an Ordered Weighted Averaging approach and study the k-sum approval voting (optimization) problem in the general case 1 ≤ k < n. For this problem, we provide different mathematical programming formulations that allow us to solve it in an exact solution framework. We provide computational results showing that our approach is efficient for medium size test problems (n up to 200, m up to 60), since in all tested cases it was able to find the exact optimal solution in very short computational times.