Igor Razgon, Leicester
A progress towards understanding the kernelizability of the multiway cut problem
A problem is parameterized if in addition to input, a parameter is
specified. A usual parameter is an upper bound on the output size. For
instance, given a graph of n vertices, find a particular subset of
vertices of size at most k. Here n is the input size and k is the
parameter.
The parameterized complexity assumes that the parameter is small compared
to the input size and asks how this assumption can be utilized for an
efficient computation. A quite radical way of the utilization is
*polynomial kernelization* or just *kernelization* for the rest of the
abstract. This is a polynomial time *preprocessing* algorithm that
shrinks the input instance to a size polynomially dependent on a parameter
(of course preserving equivalence with the original instance). When the
problem is subsequently solved, the runtime dependence on n is completely
abandoned, the runtime will depend only on the (small) parameter k. Such
preprocessing with a theoretical upper bound on the size of the resulting
instance looks very attractive from the practical point of view.
Therefore there is a lot of ongoing research related to understanding
whether a particular problem is kernelizable or probably (not). (Like in
case P vs. NP, for some problems it is possible to show that their
kernelizability leads to failure of some widely believed conjecture in the
complexity theory and hence is very unlikely.)
In this talk I will focus on the ongoing research towards understanding
the kernelizability of the *muliway cut problem* This is a natural
generalization of the well known mincut problem where we are given an
arbitrary number of terminals (not just two as in the mincut case) and
asked to remove at most k vertices or edges so that all the terminals are
separated. Understanding kernelizability of this problem is considered by
the parameterized complexity community as a challenging and interesting
question. We demonstrate that this problem is kernelizable for a special
case described below.
Given an instance of the multiway cut problem, an *isolating cut* is a set
of non-terminal vertices separating one of terminals from the rest. Let r
be the smallest size of an isolating cut. We show the the (vertex)
multiway cut problem is polynomially kernelizable if k-r=O(log k). The
solution is based on a combinatorial result that might be of an
independent interest. The corresponding preprint is available at
http://arxiv.org/abs/1104.5361
The talk will be self contained. I will start from definition of
kernelization, demonstrate a classical simple example of kernelization of
the vertex cover problem and only then turn to the above topic. I will
give an intuitive description of the related ideas without going much into
the technicalities.