Reference Hub2
An Efficient Evolutionary Algorithm for Strict Strong Graph Coloring Problem

An Efficient Evolutionary Algorithm for Strict Strong Graph Coloring Problem

Meriem Bensouyad, Nousseiba Guidoum, Djamel-Eddine Saïdouni
Copyright: © 2014 |Volume: 5 |Issue: 2 |Pages: 15
ISSN: 1942-3594|EISSN: 1942-3608|EISBN13: 9781466652408|DOI: 10.4018/ijaec.2014040102
Cite Article Cite Article

MLA

Bensouyad, Meriem, et al. "An Efficient Evolutionary Algorithm for Strict Strong Graph Coloring Problem." IJAEC vol.5, no.2 2014: pp.22-36. http://doi.org/10.4018/ijaec.2014040102

APA

Bensouyad, M., Guidoum, N., & Saïdouni, D. (2014). An Efficient Evolutionary Algorithm for Strict Strong Graph Coloring Problem. International Journal of Applied Evolutionary Computation (IJAEC), 5(2), 22-36. http://doi.org/10.4018/ijaec.2014040102

Chicago

Bensouyad, Meriem, Nousseiba Guidoum, and Djamel-Eddine Saïdouni. "An Efficient Evolutionary Algorithm for Strict Strong Graph Coloring Problem," International Journal of Applied Evolutionary Computation (IJAEC) 5, no.2: 22-36. http://doi.org/10.4018/ijaec.2014040102

Export Reference

Mendeley
Favorite Full-Issue Download

Abstract

A very promising approach for combinatorial optimization is evolutionary algorithms. As an application, this paper deals with the strict strong graph coloring problem defined by Haddad and Kheddouci (2009) where the authors have proposed an exact polynomial time algorithm for trees. The aim of this paper is to introduce a new evolutionary algorithm for solving this problem for general graphs. It combines an original crossover and a powerful correction operator. Experiments of this new approach are carried out on large Dimacs Challenge benchmark graphs. Results show very competitive with and even better than those of state of the art algorithms. To the best of the author's knowledge, it is the first time that an evolutionary algorithm is proposed to solve the strict strong graph coloring problem.

Request Access

You do not own this content. Please login to recommend this title to your institution's librarian or purchase it from the IGI Global bookstore.