Idealized dynamic population sizing for uniformly scaled problems

Genetic and Evolutionary Computation Conference, GECCO'11

Volumn , Issue , 2011, Pages 917-924

  Lobo, Fernando G ^a  

^a UNIVERSITY OF ALGARVE   (Portugal)

Author keywords

Genetic algorithms; Parameter control; Population sizing

Indexed keywords

DECOMPOSABLE PROBLEMS; DYNAMIC POPULATION; LOWER BOUNDS; PARAMETER CONTROL; POPULATION SIZING; SELF-ADJUSTING; UNIFORM SCALE;

GENETIC ALGORITHMS;

EID: 84860418410     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2001576.2001702     Document Type: Conference Paper

References (17)

1. J. Arabas, Z. Michalewicz, and J. Mulawka. GAVaPS - a genetic algorithm with varying population size. In Proc. of the First IEEE Conf. on Evolutionary Computation, pages 73-78, Piscataway, NJ, 1994. IEEE Press.
2. T. Bäck, A. E. Eiben, and N. A. L. van der Vaart. An empirical study on GAs without parameters. In Parallel Problem Solving from Nature, PPSN VI, LNCS 1917, pages 315-324. Springer, 2000.
3. J. E. Cook and D. R. Tauritz. An exploration into dynamic population sizing. In Proceedings of the Genetic and Evolutionary Computation Conference GECCO-2010, pages 807-814. ACM, 2010.
4. A. E. Eiben, E. Marchiori, and V. A. Valko. Evolutionary algorithms with on-the-fly population size adjustment. In X. Yao et al., editors, Parallel Problem Solving from Nature PPSN VIII, LNCS 3242, pages 41-50. Springer, 2004. (Pubitemid 39750205)
5. A. E. Eiben, Z. Michalewicz, M. Schoenauer, and J. E. Smith. Parameter control in evolutionary algorithms. In F. G. Lobo, C. F. Lima, and Z. Michalewicz, editors, Parameter Setting in Evolutionary Algorithms, pages 19-46. Springer, 2007.
6. W. Feller. An introduction to probability theory and its applications, volume 1. John Wiley and Sons, New York, NY, 2nd edition, 1966.
7. 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. (Pubitemid 32806319)
8. D. E. Goldberg, K. Deb, and J. H. Clark. Genetic algorithms, noise, and the sizing of populations. Complex Systems, 6:333-362, 1992.
9. G. Harik, E. Cantú-Paz, D. E. Goldberg, and B. L. Miller. The gambler's ruin problem, genetic algorithms, and the sizing of populations. Evolutionary Computation, 7(3):231-253, 1999.
10. G. R. Harik and F. G. Lobo. A parameter-less genetic algorithm. In W. Banzhaf et al., editors, Proceedings of the Genetic and Evolutionary Computation Conference GECCO-99, pages 258-265, San Francisco, CA, 1999. Morgan Kaufmann.
11. F. G. Lobo and C. F. Lima. Adaptive population sizing schemes in genetic algorithms. In F. G. Lobo, C. F. Lima, and Z. Michalewicz, editors, Parameter Setting in Evolutionary Algorithms, pages 185-204. Springer, 2007.
12. H. Mühlenbein and T. Mahning. FDA - A scalable evolutionary algorithm for the optimization of additively decomposed functions. Evolutionary Computation, 7(4):353-376, 1999.
13. M. Pelikan. Hierarchical Bayesian Optimization Algorithm: Toward a New Generation of Evolutionary Algorithms. Springer, 2005.
14. K. Sastry. Evaluation-relaxation schemes for genetic and evolutionary algorithms. Master's thesis, University of Illinois at Urbana-Champaign, Urbana, IL, 2001.
15. R. E. Smith and E. Smuda. Adaptively resizing populations: Algorithm, analysis, and first results. Complex Systems, 9:47-72, 1995. (Pubitemid 126018748)
16. E. Smorodkina and D. R. Tauritz. Greedy population sizing for evolutionary algorithms. In Proceedings of the IEEE Congress on Evolutionary Computation, CEC 2007, pages 2181-2187. IEEE, 2007.
17. T.-L. Yu, K. Sastry, and D. E. Goldberg. Online population size adjusting using noise and substructural measurements. In Proceedings of the IEEE International Conference on Evolutionary Computation, pages 2491-2498, 2005. (Pubitemid 41496160)