Memetic firefly algorithm for combinatorial optimization

Proceedings of the 5th International Conference on Bioinspired Optimization Methods and their Applications, BIOMA 2012

Volumn , Issue , 2012, Pages 75-86

  Fister, Iztok ^a,a   Brest, Janez ^a   Yang, Xin She ^b  

^a UNIVERSITY OF MARIBOR   (Slovenia)

^b NATIONAL PHYSICAL LABORATORY   (United Kingdom)

Author keywords

Firefly algorithm; Graph 3 coloring; Nature inspired algorithms; NPcomplete problem; Swarm intelligence

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BIOLUMINESCENCE; COMBINATORIAL MATHEMATICS; COMBINATORIAL OPTIMIZATION; COMPUTATIONAL COMPLEXITY; EVOLUTIONARY ALGORITHMS; GRAPH THEORY; HEURISTIC ALGORITHMS;

COMBINATORIAL OPTIMIZATION PROBLEMS; CONTINUOUS OPTIMIZATION PROBLEMS; FIREFLY ALGORITHMS; GRAPH 3 COLORINGS; HYBRID EVOLUTIONARY ALGORITHM; META HEURISTIC ALGORITHM; NATURE INSPIRED ALGORITHMS; SWARM INTELLIGENCE;

OPTIMIZATION;

EID: 84976359390     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. I. Blöchliger and N. Zufferey. A graph coloring heuristic using partial solutions and a reactive tabu scheme. Comput. Oper. Res., 35(3):960-975, 2008.
2. D. Brelaz. New methods to color vertices of a graph. Commun. ACM, 22(4):251-256, 1979.
3. P. Cheeseman, B. Kanefsky, and W. M. Taylor. Where the really hard problems are. In Proc. International Joint Conference on Artificial Intelligence, volume 1, pages 331-337, 1991.
4. M. Chiarandini and T. Stützle. An aAnalysis of heuristics for vertex colouring. Lect. Notes Comput. Sc., 6049:326-337, 2010.
5. M. Chiandini and T. Stützle. Online compendium to the article: An Analysis of Heuristics for Vertex Colouring. http://www.imada.sdu.dk/~marco/gcp-study/. Accessed at 20 March 2012.
6. J. Culberson. Graph Coloring Page. http://www.ncbi.nlm.nih.gov. Accessed at 20 March 2012.
7. M. Dorigo and T. Stützle. Ant Colony Optimization. MIT Press, 2004.
8. Á. E. Eiben, K. Hauw, and J. I. Hemert. Graph coloring with adaptive evolutionary algorithms. J. Heuristics, 4(1):25-46, 1998.
9. Á. E. Eiben and S. K. Smit. Parameter tuning for configuring and analyzing evolutionary algorithms. Swarm and Evolutionary Computation, 1(1):19-31, 2011.
10. I. Fister and J. Brest. Using differential evolution for the graph coloring. In Proc. IEEE Symposium Series on Computational Intelligence, pages 150-156, 2011.
11. I. Fister, I. Fister Jr., J. Brest, and V. Žumer. Memetic Artificial bee colony algorithm for large-scale global optimization. In Proc. IEEE Congress on Evolutionary Computation, 2012.
12. I. Fister Jr., I. Fister, and J. Brest. A hybrid artificial bee colony algorithm for graph 3-coloring. In Proc. 11th International Conference on Artificial Intelligence and Soft Computing, 2012.
13. C. Fleurent and J. Ferland. Genetic and hybrid algorithms for graph coloring. Ann. Oper. Res., 63(3):437-464, 1996.
14. P. Galinier and J. Hao. Hybrid evolutionary algorithms for graph coloring. J. Comb. Optim., 3(4):379-397, 1999.
15. P. Galinier and A. Hertz. A survey of local search methods for graph coloring. Comput. Oper. Res., 33(9):2547-2562, 2006.
16. M. R. Garey and D. S. Johnson. Computers and Intractability: A Guide to the Theory of NP-Completeness. W.H. Freeman & Co., 1979.
17. F. Glover. Future paths for integer programming and links to artificial intelligence. Comput. Oper. Res., 13(5):533-549, 1986.
18. J. I. Van Hemert. Jano's Homepage. http://www.vanhemert.co.uk/csp-ea. html. Accessed at 20 March 2012.
19. A. Hertz and D. de Werra. Using tabu search techniques for graph coloring. Computing, 39(4):345-351, 1987.
20. A. Hertz, M. Plumettaz, and N. Zufferey. Variable Space Search for Graph Coloring. Discrete Appl. Math., 156(13):2551-2560, 2008.
21. D. Karaboga and B. Basturk. A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm. J. Global Optim., 39(3):459-471, 2007.
22. J. Kennedy and R. C. Eberhart. Particle swarm optimization. In Proc. IEEE International Conference on Neural Networks, volume 4, pages 1942-1948, 1995.
23. Y. Liu and K.M. Passino. Biomimicry of social foraging bacteria for distributed optimization: Models, principles, and emergent behaviors. J. Optimiz. Theory App., 115(3):603-628, 2002.
24. Z. Lü and J. K. Hao. A memetic algorithm for graph coloring. Eur. J. Oper. Res., 203(1):241-250, 2010.
25. E. Malaguti, M. Monaci and P. Toth. A metaheuristic approach for the vertex coloring problem. INFORMS J. Comput., 20(2):302-316, 2008.
26. E. Malaguti and P. Toth. A survey on vertex coloring problems. Intl. Trans. Oper. Res., 17(1):1-34, 2009.
27. A. D. Petford and D. J. A. Welsh. A randomized 3-coloring algorithms. Discrete Math., 74(1-2):253-261, 1989.
28. X.-S. Yang. Nature-Inspired Metaheuristic Algorithms. Luniver Press, 2008
29. X.-S. Yang. Firefly Algorithm, Lévy Flights and Global Optimization. In M. Bramer, R. Ellis, and M. Petridis, editors, Springer London, Research and Development in Intelligent Systems, volume 26, pages 209-218, 2010.
30. X.-S. Yang. Firefly algorithm, stochastic test functions and design optimization. Int. J. Bio-Inspired Computation, 2(2):78-84, 2010
31. J. S. Turner. Almost all k-colorable graphs are easy to color. J. Algorithm., 9(1):63-82, 1988.