Title
On approximate data reduction for the Rural Postman Problem: Theory and experiments
Abstract
Given an undirected graph with edge weights and a subsetRof its edges, the Rural Postman Problem (RPP) is to find a closed walk of minimum total weight containing all edges ofR. We prove that RPP is WK[1]-complete parameterized by the number and weightdof edges traversed additionally to the required ones. Thus RPP instances cannot be polynomial-time compressed to instances of size polynomial indunless the polynomial-time hierarchy collapses. In contrast, denoting byb <= 2dthe number of vertices incident to an odd number of edges ofRand byc <= dthe number of connected components formed by the edges inR, we show how to reduce any RPP instanceIto an RPP instanceI(')with2b + O(c/epsilon)vertices inO(n(3))time so that any alpha-approximate solution forI(')gives an alpha(1 + epsilon)-approximate solution forI, for any alpha >= 1and epsilon > 0. That is, we provide a polynomial-size approximate kernelization scheme (PSAKS). We experimentally evaluate it on wide-spread benchmark data sets as well as on two real snow plowing instances from Berlin. We also make first steps toward a PSAKS for the parameterc.
Year
DOI
Venue
2020
10.1002/net.21985
NETWORKS
Keywords
DocType
Volume
above-guarantee parameterization,capacitated arc routing,Eulerian extension,lossy kernelization,NP-hard problem,parameterized complexity
Journal
76.0
Issue
ISSN
Citations 
4.0
0028-3045
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
René van Bevern112619.33
Till Fluschnik2267.14
O. Yu. Tsidulko312.85