Let $V$ be a set of $n$ points in $\mathbb{ R}^d$, called voters. A point $p\in \mathbb{ R}^d$ is a plurality point for $V$ when the following holds: for every $q\in\mathbb{ R}^d$ the number of voters closer to $p$ than to $q$ is at least the number of voters closer to $q$ than to $p$. Thus, in a vote where each $v\in V$ votes for the nearest proposal (and voters for which the proposals are at equal distance abstain), proposal $p$ will not lose against any alternative proposal $q$. For most voter sets a plurality point does not exist. We therefore introduce the concept of $\beta$-plurality points, which are defined similarly to regular plurality points except that the distance of each voter to $p$ (but not to $q$) is scaled by a factor $\beta$, for some constant $0<\beta\leq 1$. We investigate the existence and computation of $\beta$-plurality points, and obtain the following. * Define $\beta^*_d := \sup \{ \beta : \text{ any finite multiset $V$ in $\mathbb{ R}^d$ admits a $\beta$-plurality point} \}$. We prove that $\beta^*_2 = \sqrt{ 3}/2$, and that $1/\sqrt{ d} \leq \beta^*_d \leq \sqrt{ 3}/2$ for all $d\geq 3$. * Define $\beta(p, V) := \sup \{ \beta : \text{ $p$ is a $\beta$-plurality point for $V$}\}$. Given a voter set $V \in \mathbb{ R}^2$, we provide an algorithm that runs in $O(n \log n)$ time and computes a point $p$ such that $\beta(p, V) \geq \beta^*_2$. Moreover, for $d\geq 2$ we can compute a point $p$ with $\beta(p,V) \geq 1/\sqrt{ d}$ in $O(n)$ time. * Define $\beta(V) := \sup \{ \beta : \text{ $V$ admits a $\beta$-plurality point}\}$. We present an algorithm that, given a voter set $V$ in $\mathbb{ R}^d$, computes an $(1-\varepsilon)\cdot \beta(V)$ plurality point in time $O(\frac{ n^2}{ \varepsilon^{ 3d-2}} \cdot \log \frac{ n}{ \varepsilon^{ d-1}} \cdot \log^2 \frac { 1}{ \varepsilon})$.
Categories: cs.CG