Title :
An ACO algorithm for graph coloring problem
Author :
Salari, E. ; Eshghi, K.
Author_Institution :
Dept. of Ind. Eng., Sharif Univ. of Technol., Tehran
Abstract :
Ant colony optimization (ACO) is a well-known metaheuristic in which a colony of artificial ants cooperate in exploring good solutions to a combinatorial optimization problem. In this paper, an ACO algorithm is presented for the graph coloring problem. This ACO algorithm conforms to max-min ant system structure and exploits a local search heuristic to improve its performance. Experimental results on DIMACS test instances show improvements over existing ACO algorithms of the graph coloring problem
Keywords :
artificial life; combinatorial mathematics; graph colouring; minimax techniques; search problems; ant colony optimization; artificial ants; combinatorial optimization; graph coloring; local search heuristic; max-min ant system structure; metaheuristic; Ant colony optimization; Frequency; Genetic algorithms; Industrial engineering; Iterative algorithms; Partitioning algorithms; Remuneration; Scheduling; Simulated annealing; System testing;
Conference_Titel :
Computational Intelligence Methods and Applications, 2005 ICSC Congress on
Conference_Location :
Istanbul
Print_ISBN :
1-4244-0020-1
DOI :
10.1109/CIMA.2005.1662331
