An agent-based algorithm for generalized graph colorings

Authors:
Thang N. Bui;ThanhVu H. Nguyen
Affiliations:
The Pennsylvania State University at Harrisburg, Middletown, PA;The Pennsylvania State University at Harrisburg, Middletown, PA
Venue:
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Year:
2006

Citing 12
Cited 1

Using tabu search techniques for graph coloring

Computing
Optimization by simulated annealing: an experimental evaluation; part II, graph coloring and number partitioning

Operations Research
A still better performance guarantee for approximate graph coloring

Information Processing Letters
An Õ(n3/14)-coloring algorithm for 3-colorable graphs

Information Processing Letters
Free Bits, PCPs, and Nonapproximability---Towards Tight Results

SIAM Journal on Computing
The ant colony optimization meta-heuristic

New ideas in optimization
New methods to color the vertices of a graph

Communications of the ACM
Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993

Cliques, Coloring, and Satisfiability: Second DIMACS Implementation Challenge, Workshop, October 11-13, 1993
Genetic Search For Fixed Channel Assignment Problem With Limited Bandwidth

GECCO '02 Proceedings of the Genetic and Evolutionary Computation Conference
Heuristic methods for graph coloring problems

Proceedings of the 2005 ACM symposium on Applied computing
"Squeaky Wheel" optimization

Journal of Artificial Intelligence Research
Ant colony system: a cooperative learning approach to the traveling salesman problem

IEEE Transactions on Evolutionary Computation

Combinatorial optimization in system configuration design

Automation and Remote Control

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents an algorithm for solving a number of generalized graph coloring problems. Specifically, it gives an agent-based algorithm for the Bandwidth Coloring problem. Using a standard method for preprocessing the input, the same algorithm can also be used to solve the Multicoloring and Bandwidth Multicoloring problems. In the algorithm a number of agents, called ants, each of which colors a portion of the graph, collaborate to obtain a coloring of the entire graph. This coloring is then further improved by a local optimization algorithm. Experimental results on a set of benchmark graphs for these generalized coloring problems show that this algorithm performs very well compared to other heuristic approaches.