Analysis of exploration and exploitation in evolutionary algorithms by ancestry trees

International Journal of Innovative Computing and Applications

Volumn 3, Issue 1, 2011, Pages 11-19

  Crepinšek, Matej ^a   Mernik, Marjan ^a   Liu, Shih Hsi ^b  

^a UNIVERSITY OF MARIBOR   (Slovenia)

^b CALIFORNIA STATE UNIVERSITY   (United States)

Author keywords

Exploitation; Exploration; Multi objective 0 1 knapsack problem

Indexed keywords

COMBINATORIAL OPTIMIZATION; NATURAL RESOURCES EXPLORATION; POPULATION STATISTICS;

0/1 KNAPSACK PROBLEMS; EVOLUTION HISTORY; EVOLUTION PROCESS; EXPLOITATION; EXPLORATION AND EXPLOITATION; GENETIC STRUCTURE; TREE-BASED APPROACH; VARIATION OPERATOR;

EVOLUTIONARY ALGORITHMS;

EID: 78651321271     PISSN: 1751648X     EISSN: 17516498     Source Type: Journal    
DOI: 10.1504/IJICA.2011.037947     Document Type: Article

References (22)

1. Amor, H.B. and Rettinger, A. (2005) 'Intelligent exploration for genetic algorithms: using selforganizing maps in evolutionary computation', Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 25-29 June, pp.1531-1538, Washington DC, USA.
2. Arabas, J., Michalewicz, Z. and Mulawka, J.J. (1994) 'GAVaPS - a genetic algorithm with varying population size', Proceedings of the IEEE Conference on the Evolutionary Computation (CEC), 27-29 June, pp.73-78, Orlando, FL, USA.
3. Bäck, T. (1994) 'Selective pressure in evolutionary algorithms: a characterization of selection mechanisms', Proceedings of the IEEE Conference on Evolutionary Computation (CEC), 27-29 June, Vol. 1, pp.57-62, Orlando, FL, USA.
4. De Jong, E.D., Watson, R.A. and Pollack, J.B. (2001) 'Reducing bloat and promoting diversity using multi-objective methods', Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 7-11 July, pp.11-18, San Francisco, CA, USA.
5. Deb, K. and Goldberg, D.E. (1989) 'An investigation of niche and species formation in genetic function optimization', Proceedings of the 3rd International Conference on Genetic Algorithms (ICGA), June, pp.42-50, Fairfax, VA, USA.
6. Eiben, A. and Schippers, C. (1998) 'On evolutionary exploration and exploitation', Fundamental Informaticae, Vol. 35, Nos. 1-4, pp.35-50.
7. Eiben, A., Hinterding, R. and Michalewicz, Z. (1999) 'Parameter control in evolutionary algorithms', IEEE Transactions on Evolutionary Computation, Vol. 3, No. 2, pp.124-141.
8. Eiben, A., Marchiori, E. and Valko, V.A. (2004) 'Evolutionary algorithms with on-the-fly population size adjustment', Lecture Notes in Computer Science, Vol. 3242, pp.41-50.
9. Gallagher, M. and Yuan, B. (2006) 'A general-purpose tunable landscape generator', IEEE Transactions on Evolutionary Computation, Vol. 10, No. 5, pp.590-602.
10. Grefenstette, J.J. (1986) 'Optimization of control parameters for genetic algorithms', IEEE Transactions on Systems, Man & Cybernetics, Vol. 16, No. 1, pp.122-128.
11. Harik, G. and Lobo, F. (1999) 'A parameter-less genetic algorithm', Technical Report IlliGAL 9900, University of Illinois at Urbana-Champaign.
12. Huang, T-Y. and Chen, Y-Y (2001) 'Diversity-based selection pooling scheme in evolution strategies', Proceedings of the 16th ACM Symposium on Applied Computing (SAC), 11-14 March, pp.351-355, Las Vegas, NV, USA.
13. Liu, S-H., Mernik, M. and Bryant, B.R. (2009) 'To explore or to exploit: an entropy-driven approach for evolutionary algorithms', International Journal of Knowledge-Based and Intelligent Engineering Systems, Vol. 13, Nos. 3-4, pp.185-206.
14. Lobo, F.G., Lima, C.F. and Michalewicz, Z. (2007) 'Parameter setting in evolutionary algorithms', Studies in Computational Intelligence, Vol. 54, Springer.
15. McPhee, N.F. and Hopper, N.J. (1999) 'Analysis of genetic diversity through population history', Proceedings of the Genetic and Evolutionary Computation Conference (GECCO), 13-17 July, pp.1112-1120, Orlando, FL, USA.
16. Michalewicz, Z. (1996) Genetic Algorithms + Data Structures = Evolution Programs, Springer-Verlag.
17. Rosca, J. (1995) 'Entropy-driven adaptive representation', Proceedings of the Workshop on Genetic Programming: From Theory to Real-World Applications, 9 July, pp.23-32, Tahoe City, CA, USA.
18. Shimodaira, H. (1997) 'DCGA: a diversity control oriented genetic algorithm', Proceedings of the 2nd International Conference on Genetic Algorithms in Engineering Systems: Innovations and Applications (GALESIA), 2-4 September, pp.444-449, Glasgow, UK.
19. Smith, R.E., Forrest, S. and Perelson, A.S. (1993) 'Searching for diverse, cooperative subpopulations with genetic algorithms', Evolutionary Computation, Vol. 1, No. 2, pp.127-149.
20. Tsutsui, S., Fujimoto, Y. and Ghosh, A. (1997) 'Forking genetic algorithms: GAs with search space division schemes', Evolutionary Computation, Vol. 5, No. 1, pp.61-80.
21. Ursem, R. (2002) 'Diversity-guided evolutionary algorithms', Lecture Notes in Computer Science, Vol. 2439, pp.462-471.
22. Zitzler, E., Laumanns, M. and Thiele, L. (2002) 'SPEA2: Improving the strength Pareto evolutionary algorithm for multiobjective optimization', in Giannakoglou, K.C., et al. (Eds.): Evolutionary Methods for Design, Optimization, and Control with Application to Industrial Problems (EUROGEN 2001), CIMNE, pp.95-100.