3 research outputs found
Constant-factor approximations for asymmetric TSP on nearly-embeddable graphs
In the Asymmetric Traveling Salesperson Problem (ATSP) the goal is to find a
closed walk of minimum cost in a directed graph visiting every vertex. We
consider the approximability of ATSP on topologically restricted graphs. It has
been shown by [Oveis Gharan and Saberi 2011] that there exists polynomial-time
constant-factor approximations on planar graphs and more generally graphs of
constant orientable genus. This result was extended to non-orientable genus by
[Erickson and Sidiropoulos 2014].
We show that for any class of \emph{nearly-embeddable} graphs, ATSP admits a
polynomial-time constant-factor approximation. More precisely, we show that for
any fixed , there exist , such that ATSP on
-vertex -nearly-embeddable graphs admits a -approximation in time
. The class of -nearly-embeddable graphs contains graphs with at
most apices, vortices of width at most , and an underlying surface
of either orientable or non-orientable genus at most . Prior to our work,
even the case of graphs with a single apex was open. Our algorithm combines
tools from rounding the Held-Karp LP via thin trees with dynamic programming.
We complement our upper bounds by showing that solving ATSP exactly on graphs
of pathwidth (and hence on -nearly embeddable graphs) requires time
, assuming the Exponential-Time Hypothesis (ETH). This is
surprising in light of the fact that both TSP on undirected graphs and Minimum
Cost Hamiltonian Cycle on directed graphs are FPT parameterized by treewidth
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