AbstractAn approximation algorithm for the maximum cut problem is designed and analyzed; its performance is experimentally compared with that of a neural algorithm and that of Goemans and Williamson's algorithm. Although the guaranteed quality of our algorithm in the worst-case analysis is poor, we give experimental evidence that its average behavior is better than that of Goemans and Williamson's algorithm
The next technique we learn is designing approximation algorithms using rounding semidefinite progra...
Given an undirected graph G = (V,E), a cut in G is a subset S ⊆ V. Let S = V \S, and let E(S,S) deno...
In Lecture 2, we discussed the unweighted max cut problem and gave 2-approximation algorithms based ...
AbstractAn approximation algorithm for the maximum cut problem is designed and analyzed; its perform...
This report constitutes a close review of Williamson and Goemans ’ random-ized approximation algorit...
This thesis investigates various computational approaches to the Maximum Cut problem. It is generall...
SL,BAEb#[1 programming based approximation algorithms, such as the Goemans and Williamson approximat...
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiab...
In this paper, we consider the max-cut problem as studied by Goemans and Williamson [8]. Since the p...
In this paper, after introducing a new semidefinite programming formulation we present an improved r...
AbstractWe consider the problem of partitioning the vertices of a weighted graph into two sets of si...
We consider the problem of partitioning the vertices of a weighted graph into two sets of sizes that...
Artículo de publicación ISITrevisan [SIAM J. Comput., 41 (2012), pp. 1769-1786] presented an algorit...
Abstract: "Polynomial-time approximation algorithms with non-trivial performance guarantees are pres...
Given a graph with non-negative edge weights, the MAXCUT problem is to partition the set of vertice...
The next technique we learn is designing approximation algorithms using rounding semidefinite progra...
Given an undirected graph G = (V,E), a cut in G is a subset S ⊆ V. Let S = V \S, and let E(S,S) deno...
In Lecture 2, we discussed the unweighted max cut problem and gave 2-approximation algorithms based ...
AbstractAn approximation algorithm for the maximum cut problem is designed and analyzed; its perform...
This report constitutes a close review of Williamson and Goemans ’ random-ized approximation algorit...
This thesis investigates various computational approaches to the Maximum Cut problem. It is generall...
SL,BAEb#[1 programming based approximation algorithms, such as the Goemans and Williamson approximat...
We present randomized approximation algorithms for the maximum cut (MAX CUT) and maximum 2-satisfiab...
In this paper, we consider the max-cut problem as studied by Goemans and Williamson [8]. Since the p...
In this paper, after introducing a new semidefinite programming formulation we present an improved r...
AbstractWe consider the problem of partitioning the vertices of a weighted graph into two sets of si...
We consider the problem of partitioning the vertices of a weighted graph into two sets of sizes that...
Artículo de publicación ISITrevisan [SIAM J. Comput., 41 (2012), pp. 1769-1786] presented an algorit...
Abstract: "Polynomial-time approximation algorithms with non-trivial performance guarantees are pres...
Given a graph with non-negative edge weights, the MAXCUT problem is to partition the set of vertice...
The next technique we learn is designing approximation algorithms using rounding semidefinite progra...
Given an undirected graph G = (V,E), a cut in G is a subset S ⊆ V. Let S = V \S, and let E(S,S) deno...
In Lecture 2, we discussed the unweighted max cut problem and gave 2-approximation algorithms based ...