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Analysis and design of algorithms : double hashing and parallel graph searching
The following is in two parts, corresponding to the two separate topics in the dissertation.Probabilistic Analysis of Double HashingIn [GS78], a deep and elegant analysis shows that double hashing is asymptotically equivalent to the ideal uniform hashing up to a load factor of about 0.319. In this paper we show how a resampling technique can be used to develop a surprisingly simple proof of the result that this equivalence holds for load factors arbitrarily close to 1.Parallel Depth First Search of Planar Directed Acyclic GraphsIn 1988, Kao [Kao88] presented the first NC algorithm for the depth first search of a directed planar graph. Recently, Kao and Klein [KK90] reduced the number of processors required from O(n^4) to linear, but the time bound is O(log^8 n).We present an algorithm for the depth first search of a planar directed acyclic graph with k sources using O(n) processors and O(log k log n) time on a CRCW PRAM model. For planar dags with a single source and a single sink, we present a simple optimal algorithm which gives the depth first search in O(log n) time with O(n/log n) processors on an EREW PRAM. For a single-source multiple-sink planar dag, we have an O(log n) time O(n) processor EREW algorithm. The EREW algorithms assume that the embedding is given. A simplified variant of the depth first search of a multisource planar dag can be used to solve the single source reachability problem for a planar directed acyclic graph in O(log^2 n) time and O(n) processors on an CRCW PRAM. Since an O(log^4 n) algorithm for this problem is used as a subroutine by Kao and Klein in their depth first search for the general planar directed graph, this will lower their time bound by a factor of log^2 n. Our work uses the concept of a planar Euler tour depth first search, a depth first search in which the Euler tour around the tree is planar and crosses no tree edge. This concept may prove to be of use in other parallel algorithms for planar graphs
Two novel evolutionary formulations of the graph coloring problem
We introduce two novel evolutionary formulations of the problem of coloring
the nodes of a graph. The first formulation is based on the relationship that
exists between a graph's chromatic number and its acyclic orientations. It
views such orientations as individuals and evolves them with the aid of
evolutionary operators that are very heavily based on the structure of the
graph and its acyclic orientations. The second formulation, unlike the first
one, does not tackle one graph at a time, but rather aims at evolving a
`program' to color all graphs belonging to a class whose members all have the
same number of nodes and other common attributes. The heuristics that result
from these formulations have been tested on some of the Second DIMACS
Implementation Challenge benchmark graphs, and have been found to be
competitive when compared to the several other heuristics that have also been
tested on those graphs.Comment: To appear in Journal of Combinatorial Optimizatio
How the structure of precedence constraints may change the complexity class of scheduling problems
This survey aims at demonstrating that the structure of precedence
constraints plays a tremendous role on the complexity of scheduling problems.
Indeed many problems can be NP-hard when considering general precedence
constraints, while they become polynomially solvable for particular precedence
constraints. We also show that there still are many very exciting challenges in
this research area
Log-space Algorithms for Paths and Matchings in k-trees
Reachability and shortest path problems are NL-complete for general graphs.
They are known to be in L for graphs of tree-width 2 [JT07]. However, for
graphs of tree-width larger than 2, no bound better than NL is known. In this
paper, we improve these bounds for k-trees, where k is a constant. In
particular, the main results of our paper are log-space algorithms for
reachability in directed k-trees, and for computation of shortest and longest
paths in directed acyclic k-trees.
Besides the path problems mentioned above, we also consider the problem of
deciding whether a k-tree has a perfect macthing (decision version), and if so,
finding a perfect match- ing (search version), and prove that these two
problems are L-complete. These problems are known to be in P and in RNC for
general graphs, and in SPL for planar bipartite graphs [DKR08].
Our results settle the complexity of these problems for the class of k-trees.
The results are also applicable for bounded tree-width graphs, when a
tree-decomposition is given as input. The technique central to our algorithms
is a careful implementation of divide-and-conquer approach in log-space, along
with some ideas from [JT07] and [LMR07].Comment: Accepted in STACS 201
Exact Localisations of Feedback Sets
The feedback arc (vertex) set problem, shortened FASP (FVSP), is to transform
a given multi digraph into an acyclic graph by deleting as few arcs
(vertices) as possible. Due to the results of Richard M. Karp in 1972 it is one
of the classic NP-complete problems. An important contribution of this paper is
that the subgraphs , of all elementary
cycles or simple cycles running through some arc , can be computed in
and , respectively. We use
this fact and introduce the notion of the essential minor and isolated cycles,
which yield a priori problem size reductions and in the special case of so
called resolvable graphs an exact solution in . We show
that weighted versions of the FASP and FVSP possess a Bellman decomposition,
which yields exact solutions using a dynamic programming technique in times
and
, where , , respectively. The parameters can
be computed in , ,
respectively and denote the maximal dimension of the cycle space of all
appearing meta graphs, decoding the intersection behavior of the cycles.
Consequently, equal zero if all meta graphs are trees. Moreover, we
deliver several heuristics and discuss how to control their variation from the
optimum. Summarizing, the presented results allow us to suggest a strategy for
an implementation of a fast and accurate FASP/FVSP-SOLVER
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