Let P be a set of n points in the plane. We consider the problem of partitioning P into two subsets P1 and P2 such that the sum of the perimeters of ch(P1) and ch(P2) is minimized, where ch(Pi) denotes the convex hull of Pi. The problem was first studied by Mitchell and Wynters in 1991 who gave an O(n 2 ) time algorithm. Despite considerable progress on related problems, no subquadratic time algorithm for this problem was found so far. We present an exact algorithm solving the problem in O(n log 4 n) time and a (1 + ε)-approximation algorithm running in O(n + 1/ε 2 · log 4 (1/ε)) time.

Let V be a set of n points in R d , which we call voters. A point p ∈ R d is preferred over another point p ′ ∈ R d by a voter υ ∈ V if dist(υ, p ) < dist(υ, p ′). A point p is called a plurality point if it is preferred by at least as many voters as any other point  p ′. We present an algorithm that decides in O ( n log n ) time whether V admits a plurality point in the L 2 norm and, if so, finds the (unique) plurality point. We also give efficient algorithms to compute a minimum-cost subset W ⊂ V such that V \ W admits a plurality point, and to compute a so-called minimum-radius plurality ball. Finally, we consider the problem in the personalized L 1 norm, where each point υ ∈ V has a preference vector 〈 w 1 (υ),…, w d (υ)〉 and the distance from υ to any point p ∈ R d is given by ∑ i =1 d w i (υ)· | x i (υ)− x i ( p )|. For this case we can compute in O ( n d −1 ) time the set of all plurality points of  V . When all preference vectors are equal, the running time improves to O ( n ).

We consider very natural "fence enclosure" problems studied by Capoyleas, Rote, and Woeginger and Arkin, Khuller, and Mitchell in the early 90s. Given a set S of n points in the plane, we aim at finding a set of closed curves such that (1) each point is enclosed by a curve and (2) the total length of the curves is minimized. We consider two main variants. In the first variant, we pay a unit cost per curve in addition to the total length of the curves. An equivalent formulation of this version is that we have to enclose n unit disks, paying only the total length of the enclosing curves. In the other variant, we are allowed to use at most k closed curves and pay no cost per curve.For the variant with at most k closed curves, we present an algorithm that is polynomial in both n and k. For the variant with unit cost per curve, or unit disks, we present a near-linear time algorithm.Capoyleas, Rote, and Woeginger solved the problem with at most k curves in n O(k) time. Arkin, Khuller, and Mitchell used this to solve the unit cost per curve version in exponential time. At the time, they conjectured that the problem with k curves is NP-hard for general k. Our polynomial time algorithm refutes this unless P equals NP.

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