Single-peakedness and total unimodularity: New polynomial-time algorithms for multi-winner elections

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Abstract

The winner determination problems of many attractive multiwinner voting rules are NP-complete. However, they often admit polynomial-time algorithms when restricting inputs to be single-peaked. Commonly, such algorithms employ dynamic programming along the underlying axis. We introduce a new technique: carefully chosen integer linear programming (IP) formulations for certain voting problems admit an LP relaxation which is totally unimodular if preferences are single-peaked, and which thus admits an integral optimal solution. This technique gives efficient algorithms for finding optimal committees under Proportional Approval Voting (PAV) and the Chamberlin-Courant rule with single-peaked preferences, as well as for certain OWA-based rules. For PAV, this is the first technique able to efficiently find an optimal committee when preferences are single-peaked. An advantage of our approach is that no special-purpose algorithm needs to be used to exploit structure in the input preferences: any standard IP solver will terminate in the first iteration if the input is single-peaked, and will continue to work otherwise.

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APA

Peters, D. (2018). Single-peakedness and total unimodularity: New polynomial-time algorithms for multi-winner elections. In 32nd AAAI Conference on Artificial Intelligence, AAAI 2018 (pp. 1169–1176). AAAI press. https://doi.org/10.1609/aaai.v32i1.11460

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