Intelligent exploration for genetic algorithms: Using self-organizing maps in evolutionary computation

GECCO 2005 - Genetic and Evolutionary Computation Conference

Volumn , Issue , 2005, Pages 1531-1538

  Amor, Heni Ben ^a   Rettinger, Achim ^a  

^a University of Koblenz   (Germany)

Author keywords

Diversity; Exploration vs. Exploitation; Genetic Algorithm; Genetic Drift; Premature Convergence; Self Organizing Map

Indexed keywords

COMPUTATION THEORY; DATA MINING; INTELLIGENT CONTROL; PROBLEM SOLVING;

DIVERSITY; EXPLORATION VS. EXPLOITATION; GENETIC DRIFT; PREMATURE CONVERGENCE; SELF-ORGANIZING MAP;

GENETIC ALGORITHMS;

EID: 32444449757     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1068009.1068250     Document Type: Conference Paper

References (14)

1. L. Eschelman and J. Schaffer. Preventing premature convergence in genetic algorithms by preventing incest. In Proceedings of the Fourth International Conference on Genetic Algorithms, pages 115-122. Morgan Kaufmann, 1991.
2. L. Eshelman. The chc adaptive search algorithm: How to have safe search when engaging in nontraditional genetic recombination. In Foundations of Genetic Algorithms, pages 256-283. Morgan Kaufmann, 1991.
3. C. Fernandes and A. Rosa. A study on non-random mating and varying population size in genetic algorithms using a royal road function. In Proceedings of the 2001 Congress on Evolutionary Computation CEC2001, pages 60-66. IEEE Press, 2001.
4. D. Fogel. An introduction to simulated evolutionary optimization. IEEE Transaction on Neural Networks, 5(1):3-14, 1994.
5. D. A. Goldberg. Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, 1989.
6. J. Hu, K. Seo, Z. Fan, R. Rosenberg, and E. Goodman. Hemo: A sustainable multi-objective evolutionary optimization framework. In Proc. 2003 Genetic and Evolutionary Computing Conference. Springer Verlag, July 2003.
7. T. Kohonen, T. Kohonen, M. R. Schroeder, and T. S. Huang. Self-Organizing Maps. Springer-Verlag New York, Inc., 2001.
8. M. Lozano, F. Herrera, and J.R.Cano. Replacement strategies to preserve useful diversity in steady-state genetic algorithms. In Press, March 2004.
9. S. W. Mahfoud. Niching methods for genetic algorithms. PhD thesis, University of Illinois at Urbana-Champaign, Urbana, IL, USA, 1995.
10. M. Mitchell, S. Forrest, and J. H. Holland. The royal road for genetic algorithms: Fitness landscapes and ga performance. In F. J. Varela and P. Bourgine, editors, Toward a Practice of Autonomous System: Proceedings of the First European Conference on Artificial Life, pages 245-254, 1991.
11. K. Rasheed. GADO: A Genetic Algorithm for Continuous Design Optimization. PhD thesis, Rutgers University, New Brunswick, NJ, 1998.
12. G. Romero, J.J.Merelo, P. Castillo, J.G.Castellano, and M. Arenas. Genetic algorithm visualization using self-organizing maps. In Parallel Problem Solving from Nature - PPSN VII, pages 442-451. Springer Verlag, 2002.
13. E. Ronald. When selection meets seduction. In Proceedings of the Sixth International Conference on Genetic Algorithms. Morgan Kaufmann, 1995.
14. B. Sareni and L. Kraehenbuehl. Fitness sharing and niching methods revisited. IEEE Transaction on Evolutionary Computation, 2(3):97-106, September 1998.