Effects of population size on performance of genetic algorithms and roles of crossover and mutation

Proceedings of the 13th International Symposium on Artificial Life and Robotics, AROB 13th'08

Volumn , Issue , 2008, Pages 861-864

  Zhang, Yu An ^a   Sakamoto, Makoto ^a   Furutani, Hiroshi ^a  

^a UNIVERSITY OF MIYAZAKI   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

CROSSOVER AND MUTATION; FAILURE PROBABILITY; FINITE POPULATION; OPTIMUM SOLUTION; POPULATION SIZES; SCHEMA THEORY; STOCHASTIC TREATMENT; WRIGHT-FISHER MODELS;

MARKOV PROCESSES; POPULATION STATISTICS; ROBOTICS; STOCHASTIC MODELS; STOCHASTIC SYSTEMS;

GENETIC ALGORITHMS;

EID: 57649231633     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (6)

1. H. Furutani, S. Katayama, M. Sakamoto and M. Ito: Stochastic Analysis of Schema Distribution in a Multiplicative Landscape, Artificial Life and Robotics, 11, (2007) 101-104
2. H. Furutani, T. Fujimaru, Y. Zhang and M. Sakamoto: Effects of Population Size on Computational Performance of Genetic Algorithm on Multiplicative Landscape, Proceedings of Third International Conference on Natural Computation, Vol.3, 488-493 (2007).
3. J. W. J. Ewens: Mathematical Population Genetics. I. Theoretical Introduction, Second Edition. Springer-Verlag, New York (2004)
4. H. Asoh and H. Mühlenbein: On the Mean Convergence Time of Evolutionary Algorithms without Selection and Mutation. Parallel Problem Solving from Nature, Lecture Notes in Computer Science, 866, Springer-Verlag, New York, (1994) 88-97
5. H. Furutani: Schema Analysis of OneMax Problem, Foundations of Genetic Algorithms 7, Morgan Kaufmann, San Francisco, (2003), 9-26
6. H. Furutani: Schema Analysis of Genetic Algorithms on Multiplicative Landscape, Proceedings of the Simulated Evolution and Learning Conference, SEAL'02, (2002) 230-235