Abstract

ROSETE-SUAREZ, Alejandro. Efficient reformulation of the linear programming rank aggregation problem. Ing. Ind. [online]. 2018, vol.39, n.3, pp. 250-260. ISSN 1815-5936.

Rankings are very commonly used to express preferences in music, sports, politics and other diverse fields. The Rank Aggregation Problem consists on finding the permutation that best represents a set of input rankings, by minimizing the Kendall distance. There is an Integer Linear Programming formulation for this problem that allows solving it in an exact way, if computational resources are available. In this paper we introduce a new Integer Linear Programming formulation of the Rank Aggregation Problem that allows reducing the number of variables by half and the amount of constraints approximately to a third part. This reduction allows solving the same problems with an improved computational efficiency.

Keywords : rank aggregation; integer linear programming; Kendall distance.

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