163 research outputs found
A LP approximation for the Tree Augmentation Problem
In the Tree Augmentation Problem (TAP) the goal is to augment a tree by a
minimum size edge set from a given edge set such that is
-edge-connected. The best approximation ratio known for TAP is . In the
more general Weighted TAP problem, should be of minimum weight. Weighted
TAP admits several -approximation algorithms w.r.t. to the standard cut
LP-relaxation, but for all of them the performance ratio of is tight even
for TAP. The problem is equivalent to the problem of covering a laminar set
family. Laminar set families play an important role in the design of
approximation algorithms for connectivity network design problems. In fact,
Weighted TAP is the simplest connectivity network design problem for which a
ratio better than is not known. Improving this "natural" ratio is a major
open problem, which may have implications on many other network design
problems. It seems that achieving this goal requires finding an LP-relaxation
with integrality gap better than , which is a long time open problem even
for TAP. In this paper we introduce such an LP-relaxation and give an algorithm
that computes a feasible solution for TAP of size at most times the
optimal LP value. This gives some hope to break the ratio for the weighted
case. Our algorithm computes some initial edge set by solving a partial system
of constraints that form the integral edge-cover polytope, and then applies
local search on -leaf subtrees to exchange some of the edges and to add
additional edges. Thus we do not need to solve the LP, and the algorithm runs
roughly in time required to find a minimum weight edge-cover in a general
graph.Comment: arXiv admin note: substantial text overlap with arXiv:1507.0279
Approximating Source Location and Star Survivable Network Problems
In Source Location (SL) problems the goal is to select a mini-mum cost source
set such that the connectivity (or flow) from
to any node is at least the demand of . In many SL problems
if , namely, the demand of nodes selected to is
completely satisfied. In a node-connectivity variant suggested recently by
Fukunaga, every node gets a "bonus" if it is selected to
. Fukunaga showed that for undirected graphs one can achieve ratio for his variant, where is the maximum demand. We
improve this by achieving ratio \min\{p^*\lnk,k\}\cdot O(\ln (k/q^*)) for a
more general version with node capacities, where is
the maximum bonus and is the minimum capacity. In
particular, for the most natural case considered by Fukunaga, we
improve the ratio from to . We also get ratio
for the edge-connectivity version, for which no ratio that depends on only
was known before. To derive these results, we consider a particular case of the
Survivable Network (SN) problem when all edges of positive cost form a star. We
give ratio for this variant, improving over the best
ratio known for the general case of Chuzhoy and Khanna
LP-Relaxations for Tree Augmentation
In the Tree Augmentation Problem (TAP) the goal is to augment a tree T by a minimum size edge set F from a given edge set E such that T+F is 2-edge-connected. The best approximation ratio known for TAP is 1.5. In the more general Weighted TAP problem, F should be of minimum weight. Weighted TAP admits several 2-approximation algorithms w.r.t. the standard cut-LP relaxation. The problem is equivalent to the problem of covering a laminar set family. Laminar set families play an important role in the design of approximation algorithms for connectivity network design problems. In fact, Weighted TAP is the simplest connectivity network design problem for which a ratio better than 2 is not known. Improving this "natural" ratio is a major open problem, which may have implications on many other network design problems. It seems that achieving this goal requires finding an LP-relaxation with integrality gap better than 2, which is an old open problem even for TAP. In this paper we introduce two different LP-relaxations, and for each of them give a simple algorithm that computes a feasible solution for TAP of size at most 7/4 times the optimal LP value. This gives some hope to break the ratio 2 for the weighted case
Approximating minimum cost connectivity problems
We survey approximation algorithms of connectivity problems.
The survey presented describing various techniques. In the talk the following techniques and results are presented.
1)Outconnectivity: Its well known that there exists a polynomial time algorithm to solve the problems of finding an edge k-outconnected from r subgraph [EDMONDS] and a vertex k-outconnectivity subgraph from r [Frank-Tardos] .
We show how to use this to obtain a ratio 2 approximation for the min cost edge k-connectivity
problem.
2)The critical cycle theorem of Mader: We state a fundamental theorem of Mader and use it to provide a 1+(k-1)/n ratio approximation for the min cost vertex k-connected subgraph, in the metric case.
We also show results for the min power vertex k-connected problem using this lemma.
We show that the min power is equivalent to the min-cost case with respect to approximation.
3)Laminarity and uncrossing: We use the well known laminarity of a BFS solution and show a simple new proof due to Ravi et al for Jain\u27s 2 approximation for Steiner network
Matroid Secretary for Regular and Decomposable Matroids
In the matroid secretary problem we are given a stream of elements and asked
to choose a set of elements that maximizes the total value of the set, subject
to being an independent set of a matroid given in advance. The difficulty comes
from the assumption that decisions are irrevocable: if we choose to accept an
element when it is presented by the stream then we can never get rid of it, and
if we choose not to accept it then we cannot later add it. Babaioff, Immorlica,
and Kleinberg [SODA 2007] introduced this problem, gave O(1)-competitive
algorithms for certain classes of matroids, and conjectured that every matroid
admits an O(1)-competitive algorithm. However, most matroids that are known to
admit an O(1)-competitive algorithm can be easily represented using graphs
(e.g. graphic and transversal matroids). In particular, there is very little
known about F-representable matroids (the class of matroids that can be
represented as elements of a vector space over a field F), which are one of the
foundational matroid classes. Moreover, most of the known techniques are as
dependent on graph theory as they are on matroid theory. We go beyond graphs by
giving an O(1)-competitive algorithm for regular matroids (the class of
matroids that are representable over every field), and use techniques that are
matroid-theoretic rather than graph-theoretic. We use the regular matroid
decomposition theorem of Seymour to decompose any regular matroid into matroids
which are either graphic, cographic, or isomorphic to R_{10}, and then show how
to combine algorithms for these basic classes into an algorithm for regular
matroids. This allows us to generalize beyond regular matroids to any class of
matroids that admits such a decomposition into classes for which we already
have good algorithms. In particular, we give an O(1)-competitive algorithm for
the class of max-flow min-cut matroids.Comment: 21 page
A greedy approximation algorithm for the group Steiner problem
AbstractIn the group Steiner problem we are given an edge-weighted graph G=(V,E,w) and m subsets of vertices {gi}i=1m. Each subset gi is called a group and the vertices in ⋃igi are called terminals. It is required to find a minimum weight tree that contains at least one terminal from every group.We present a poly-logarithmic ratio approximation for this problem when the input graph is a tree. Our algorithm is a recursive greedy algorithm adapted from the greedy algorithm for the directed Steiner tree problem [Approximating the weight of shallow Steiner trees, Discrete Appl. Math. 93 (1999) 265–285, Approximation algorithms for directed Steiner problems, J. Algorithms 33 (1999) 73–91]. This is in contrast to earlier algorithms that are based on rounding a linear programming based relaxation for the problem [A polylogarithmic approximation algorithm for the Group Steiner tree problem, J. Algorithms 37 (2000) 66–84, preliminary version in Proceedings of SODA, 1998 pp. 253–259, On directed Steiner trees, Proceedings of SODA, 2002, pp. 59–63]. We answer in positive a question posed in [A polylogarithmic approximation algorithm for the Group Steiner tree problem, J. Algorithms 37 (2000) 66–84, preliminary version in Proceedings of SODA, 1998 pp. 253–259] on whether there exist good approximation algorithms for the group Steiner problem that are not based on rounding linear programs. For every fixed constant ε>0, our algorithm gives an O((log∑i|gi|)1+ε·logm) approximation in polynomial time. Approximation algorithms for trees can be extended to arbitrary undirected graphs by probabilistically approximating the graph by a tree. This results in an additional multiplicative factor of O(log|V|) in the approximation ratio, where |V| is the number of vertices in the graph. The approximation ratio of our algorithm on trees is slightly worse than the ratio of O(log(maxi|gi|)·logm) provided by the LP based approaches
- …