In this paper we present a novel coloring algorithm based on local search. We analyze its performance, and report several experimental results on DIMACS benchmark graphs. From our experiments, this algorithm looks robust, and yields a substantial speed up on previous algorithms for coloring. Our algorithm improves the best known coloring for four different DIMACS benchmark graphs: namely, Le450-25c, Le450-25d and Flat300_28_0 and Flat1000_76_0. Furthermore, we have run experiments on a simulator to get insights on its cache consciousness: from these experiments, it appears that the algorithm performs substantially less cache misses than other existing algorithms
The Graph Colouring Problem (GCP) is a well known N P-hard problem with many theoretical and practic...
This paper presents an improved probability learning based local search algorithm for the well-known...
The weighted graph coloring problem (WGCP) is an important extension of the graph coloring problem (...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
AbstractIn this paper we present a novel coloring algorithm based on local search. We analyze its pe...
AbstractIn this paper we present a novel coloring algorithm based on local search. We analyze its pe...
AbstractIn this paper we present a novel coloring algorithm based on local search. We analyze its pe...
In this paper a fast and simple local search algorithm for graph coloring is presented. The algorith...
Local search (LS) is a widely used, general approach for solving hard combinatorial search problems,...
. This paper presents a new genetic local search algorithm for the graph coloring problem. The algor...
Abstract. Graph coloring is a well known problem from graph theory that, when attacking it with loca...
The Graph Colouring Problem (GCP) is a well known N P-hard problem with many theoretical and practic...
This paper presents an improved probability learning based local search algorithm for the well-known...
The weighted graph coloring problem (WGCP) is an important extension of the graph coloring problem (...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
In this paper we present a novel coloring algorithm based on local search. We analyze its performanc...
AbstractIn this paper we present a novel coloring algorithm based on local search. We analyze its pe...
AbstractIn this paper we present a novel coloring algorithm based on local search. We analyze its pe...
AbstractIn this paper we present a novel coloring algorithm based on local search. We analyze its pe...
In this paper a fast and simple local search algorithm for graph coloring is presented. The algorith...
Local search (LS) is a widely used, general approach for solving hard combinatorial search problems,...
. This paper presents a new genetic local search algorithm for the graph coloring problem. The algor...
Abstract. Graph coloring is a well known problem from graph theory that, when attacking it with loca...
The Graph Colouring Problem (GCP) is a well known N P-hard problem with many theoretical and practic...
This paper presents an improved probability learning based local search algorithm for the well-known...
The weighted graph coloring problem (WGCP) is an important extension of the graph coloring problem (...