9 research outputs found
Planar Capacitated Dominating Set Is W[1]-Hard
Given a graph G together with a capacity function c: V (G) â\u86\u92 N, we call S â\u8a\u86 V (G) a capacitated dominating set if there exists a mapping f: (V (G) \ S) â\u86\u92 S which maps every vertex in (V (G) \ S) to one of its neighbors such that the total number of vertices mapped by f to any vertex v â\u88\u88 S does not exceed c(v). In the Planar Capacitated Dominating Set problem we are given a planar graph G, a capacity function c and a positive integer k and asked whether G has a capacitated dominating set of size at most k. In this paper we show that Planar Capacitated Dominating Set is W[1]-hard, resolving an open problem of Dom et al. [IWPEC, 2008]. This is the first bidimensional problem to be shown W[1]-hard. Thus Planar Capacitated Dominating Set can become a useful starting point for reductions showing parameterized intractablility of planar graph problems
On the computational tractability of a geographic clustering problem arising in redistricting
Redistricting is the problem of dividing a state into a number of
regions, called districts. Voters in each district elect a representative. The
primary criteria are: each district is connected, district populations are
equal (or nearly equal), and districts are "compact". There are multiple
competing definitions of compactness, usually minimizing some quantity.
One measure that has been recently promoted by Duchin and others is number of
cut edges. In redistricting, one is given atomic regions out of which each
district must be built. The populations of the atomic regions are given.
Consider the graph with one vertex per atomic region (with weight equal to the
region's population) and an edge between atomic regions that share a boundary.
A districting plan is a partition of vertices into parts, each connnected,
of nearly equal weight. The districts are considered compact to the extent that
the plan minimizes the number of edges crossing between different parts.
Consider two problems: find the most compact districting plan, and sample
districting plans under a compactness constraint uniformly at random. Both
problems are NP-hard so we restrict the input graph to have branchwidth at most
. (A planar graph's branchwidth is bounded by its diameter.) If both and
are bounded by constants, the problems are solvable in polynomial time.
Assume vertices have weight~1. One would like algorithms whose running times
are of the form for some constant independent of and
, in which case the problems are said to be fixed-parameter tractable with
respect to and ). We show that, under a complexity-theoretic assumption,
no such algorithms exist. However, we do give algorithms with running time
. Thus if the diameter of the graph is moderately small and the
number of districts is very small, our algorithm is useable
Tight bounds for planar strongly connected Steiner subgraph with fixed number of terminals (and extensions)
(see paper for full abstract)
Given a vertex-weighted directed graph and a set of terminals, the objective of the SCSS problem is to find a
vertex set of minimum weight such that contains a
path for each . The problem is NP-hard, but
Feldman and Ruhl [FOCS '99; SICOMP '06] gave a novel algorithm for
the SCSS problem, where is the number of vertices in the graph and is
the number of terminals. We explore how much easier the problem becomes on
planar directed graphs:
- Our main algorithmic result is a algorithm
for planar SCSS, which is an improvement of a factor of in the
exponent over the algorithm of Feldman and Ruhl.
- Our main hardness result is a matching lower bound for our algorithm: we
show that planar SCSS does not have an algorithm
for any computable function , unless the Exponential Time Hypothesis (ETH)
fails.
The following additional results put our upper and lower bounds in context:
- In general graphs, we cannot hope for such a dramatic improvement over the
algorithm of Feldman and Ruhl: assuming ETH, SCSS in general graphs
does not have an algorithm for any computable
function .
- Feldman and Ruhl generalized their algorithm to the more general
Directed Steiner Network (DSN) problem; here the task is to find a subgraph of
minimum weight such that for every source there is a path to the
corresponding terminal . We show that, assuming ETH, there is no
time algorithm for DSN on acyclic planar graphs.Comment: To appear in SICOMP. Extended abstract in SODA 2014. This version has
a new author (Andreas Emil Feldmann), and the algorithm is faster and
considerably simplified as compared to conference versio