单峰性和全单模性：多赢家选举的新多项式时间算法
Single-Peakedness and Total Unimodularity: New Polynomial-Time Algorithms for Multi-Winner Elections
摘要：
许多有吸引力的多赢家投票规则的赢家确定问题是NP完全的。然而，当限制输入为单峰时，它们通常允许多项式时间算法。通常，这样的算法采用沿基础轴的动态规划。我们介绍一种新技术：仔细选择整数线性规划（IP）公式为某些投票问题承认的LP松弛，这是完全么模，如果偏好是单峰，因此承认一个积分最优解。这种技术提供了有效的算法，找到最佳的委员会比例批准投票（PAV）和Chamberlin-Courant规则与单峰的偏好，以及某些OWA为基础的规则。对于PAV，这是第一个能够有效地找到一个最佳的委员会时，偏好是单峰的技术。我们的方法的一个优点是，不需要使用特殊用途的算法来利用输入偏好中的结构：如果输入是单峰的，则任何标准的IP求解器将在第一次迭代中终止，否则将继续工作。
英文摘要：
The winner determination problems of many attractive multi-winner 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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