Balancing graph Voronoi diagrams with one more vertex

Abstract

Let G=(V,E)G=(V,E) be a graph with unit-length edges and nonnegative costs assigned to its vertices. Being given a list of pairwise different vertices S=(s1,s2,…,sp)S=(s_1,s_2,\ldots,s_p), the {\em prioritized Voronoi diagram} of GG with respect to SS is the partition of GG in pp subsets V1,V2,…,VpV_1,V_2,\ldots,V_p so that, for every ii with 1≀i≀p1 \leq i \leq p, a vertex vv is in ViV_i if and only if sis_i is a closest vertex to vv in SS and there is no closest vertex to vv in SS within the subset {s1,s2,…,siβˆ’1}\{s_1,s_2,\ldots,s_{i-1}\}. For every ii with 1≀i≀p1 \leq i \leq p, the {\em load} of vertex sis_i equals the sum of the costs of all vertices in ViV_i. The load of SS equals the maximum load of a vertex in SS. We study the problem of adding one more vertex vv at the end of SS in order to minimize the load. This problem occurs in the context of optimally locating a new service facility ({\it e.g.}, a school or a hospital) while taking into account already existing facilities, and with the goal of minimizing the maximum congestion at a site. There is a brute-force algorithm for solving this problem in O(nm){\cal O}(nm) time on nn-vertex mm-edge graphs. We prove a matching time lower bound for the special case where m=n1+o(1)m=n^{1+o(1)} and p=1p=1, assuming the so called Hitting Set Conjecture of Abboud et al. On the positive side, we present simple linear-time algorithms for this problem on cliques, paths and cycles, and almost linear-time algorithms for trees, proper interval graphs and (assuming pp to be a constant) bounded-treewidth graphs

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