We present an extension to a hybrid graph-bisection algorithm developed by Bui et al. that uses vertex coalescing and the Kernighan-Lin variable-depth algorithm to minimize the size of the cut set. In the original heuristic technique, one iteration of vertex coalescing is used to improve the performance of the original Kernighan-Lin algorithm. We show that by performing vertex coalescing recursively, substantially greater improvements can be achieved for standard random graphs of average degree in the range [2:0; 5:0].Engineering and Applied Science
AbstractThe bisection width b(G) of a graph G is the number of edges necessary in an edge cut of G s...
In the family of clustering problems we are given a set of objects (vertices of the graph), together...
We resolve in the affirmative a question of R.B. Boppana and T. Bui: whether simulated annealing can...
We present an extension to a hybrid graph-bisection algorithm developed by Bui et al. that uses vert...
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clustering....
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clustering....
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clus-tering...
We investigate a family of algorithms for graph bisection that are based on a simple local connectiv...
We describe a new, linear time heuristic for the improvement of graph bisections. The method is a va...
We investigate the statistical properties of cut sizes generated by heuristic algorithms which solve...
Abstract. The Bisection problem asks for a partition of the vertices of a graph into two equally siz...
Partitioning graphs into equally large groups of nodes while minimizing the number of edges between ...
We resolve in the affirmative a question of Boppana and Bui: whether simulated annealing can, with h...
We resolve in the affirmative a question of Boppana and Bui: whether simulated annealing can, with h...
We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partiti...
AbstractThe bisection width b(G) of a graph G is the number of edges necessary in an edge cut of G s...
In the family of clustering problems we are given a set of objects (vertices of the graph), together...
We resolve in the affirmative a question of R.B. Boppana and T. Bui: whether simulated annealing can...
We present an extension to a hybrid graph-bisection algorithm developed by Bui et al. that uses vert...
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clustering....
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clustering....
We present a new heuristic algorithm for graph bisection, based on an implicit notion of clus-tering...
We investigate a family of algorithms for graph bisection that are based on a simple local connectiv...
We describe a new, linear time heuristic for the improvement of graph bisections. The method is a va...
We investigate the statistical properties of cut sizes generated by heuristic algorithms which solve...
Abstract. The Bisection problem asks for a partition of the vertices of a graph into two equally siz...
Partitioning graphs into equally large groups of nodes while minimizing the number of edges between ...
We resolve in the affirmative a question of Boppana and Bui: whether simulated annealing can, with h...
We resolve in the affirmative a question of Boppana and Bui: whether simulated annealing can, with h...
We present a novel exact algorithm for the minimum graph bisection problem, whose goal is to partiti...
AbstractThe bisection width b(G) of a graph G is the number of edges necessary in an edge cut of G s...
In the family of clustering problems we are given a set of objects (vertices of the graph), together...
We resolve in the affirmative a question of R.B. Boppana and T. Bui: whether simulated annealing can...