TY - GEN
T1 - Solving graph coloring problem by fuzzy clustering-based genetic algorithm
AU - Lee, Young Seol
AU - Cho, Sung Bae
PY - 2012
Y1 - 2012
N2 - The graph coloring problem is one of famous combinatorial optimization problems. Some researchers attempted to solve combinatorial optimization problem with evolutionary algorithm, which can find near optimal solution based on the evolution mechanism of the nature. However, it sometimes requires too much cost to evaluate fitness of a large number of individuals in the population when applying the GA to the real world problems. This paper attempts to solve graph coloring problem using a fuzzy clustering based evolutionary approach to reduce the cost of the evaluation. In order to show the feasibility of the method, some experiments with other alternative methods are conducted.
AB - The graph coloring problem is one of famous combinatorial optimization problems. Some researchers attempted to solve combinatorial optimization problem with evolutionary algorithm, which can find near optimal solution based on the evolution mechanism of the nature. However, it sometimes requires too much cost to evaluate fitness of a large number of individuals in the population when applying the GA to the real world problems. This paper attempts to solve graph coloring problem using a fuzzy clustering based evolutionary approach to reduce the cost of the evaluation. In order to show the feasibility of the method, some experiments with other alternative methods are conducted.
UR - http://www.scopus.com/inward/record.url?scp=84871363027&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84871363027&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-34859-4_35
DO - 10.1007/978-3-642-34859-4_35
M3 - Conference contribution
AN - SCOPUS:84871363027
SN - 9783642348587
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 351
EP - 360
BT - Simulated Evolution and Learning - 9th International Conference, SEAL 2012, Proceedings
T2 - 9th International Conference on Simulated Evolution and Learning, SEAL 2012
Y2 - 16 December 2012 through 19 December 2012
ER -