Adaptive evolutionary algorithm based on population dynamics for dynamic environments

Genetic and Evolutionary Computation Conference, GECCO'11

Volumn , Issue , 2011, Pages 909-916

  Gouvêa Jr , Maury M ^a   Araújo, Aluizio F R ^b  

^a PONTIFICAL CATHOLIC UNIVERSITY OF MINAS GERAIS   (Brazil)

^b FEDERAL UNIVERSITY OF PERNAMBUCO   (Brazil)

Author keywords

Adaptive control; Diversity; Evolutionary algorithms; Population dynamics

Indexed keywords

ADAPTIVE CONTROL; ADJUSTABLE PARAMETERS; BLACK BOXES; CONTROL PROBLEMS; CONTROL VARIABLE; DIVERSITY; DIVERSITY LEVEL; DYNAMIC ENVIRONMENTS; EVOLUTIONARY PROCESS; POPULATION DIVERSITY; POPULATION DYNAMICS MODELS; PROCESS INPUTS; PROCESS OUTPUT;

ADAPTIVE ALGORITHMS; ADAPTIVE CONTROL SYSTEMS; POPULATION DYNAMICS; SENSITIVITY ANALYSIS;

EVOLUTIONARY ALGORITHMS;

EID: 84860404047     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2001576.2001701     Document Type: Conference Paper

References (25)

1. K. J. Aström and B. Wittenmark. Adaptive Control. Addison-Wesley, 2 edition, 1995.
2. J. Branke and H. Schmeck. Designing Evolutionary Algorithms for Dynamic Optimization Problems. Advances in Evolutionary Computing: Theory and Applications, 2003.
3. H. G. Cobb. An investigation into the use of hypermutation as an adaptive operator in genetic algorithms having continuous, time-dependent nonstationary environments. Technical Report Technical Rep. AIC-90-001, Naval Research Laboratory, Washington, 1990.
4. J. F. Crow and M. Kimura. An Introduction to Population Genetic Theory. Burgess Publishing, Minnesota, 1970.
5. R. A. Fisher. The Genetical Theory of Natural Selection. Oxford University Press, 1930.
6. M. M. Gouvêa Jr. and A. F. R. Araújo. Diversity-based model reference for genetic algorithms in dynamic environment. In 2007 IEEE Congress on Evolutionary Computation, CEC'07, Singapore, South Korea, September, 25-28 2007. IEEE Press.
7. M. M. Gouvêa Jr. and A. F. R. Araújo. Diversity control based on population heterozygosity dynamic. In 2008 IEEE Congress on Evolutionary Computation, CEC'08, Hong Kong, 2008.
8. M. M. Gouvêa Jr. and A. F. R. Araújo. Population dynamic model for gene frequency prediction in evolutionary algorithms. In 2008 IEEE Congress on Evolutionary Computation, CEC'08, Hong Kong, 2008.
9. J. J. Grefenstette. Genetic algorithms for changing environments, volume 2, pages 137-144. North-Holland, 1992.
10. F. Herrera and M. Lozano. Two-loop real-coded genetic algorithms with adaptive control of mutation step sizes. Applied Intelligence, 13(3):187-204, nov 2000.
11. Y. Jin and J. Branke. Evolutionary optimization in uncertain environments: a survey. IEEE Transactions on Evolutionary Computation, 9(3):303-317, 2005. (Pubitemid 40871134)
12. P. Leberg. Genetic approaches for estimating the effective size of populations. Journal of Wildlife Management, 69(4):1385-1399, 2005.
13. A. E. Magurran. Measuring Biological Diversity. Blackwell, Oxford, UK, 2004.
14. R. W. Morrison. Designing Evolutionary Algorithms for Dynamic Environments. Springer, Berlin, 2004.
15. M. K. Schwartz, D. A. Tallmon, and G. Luikart. Review of DNA-based census and effective population size estimators. Animal Conservation, 1:293-299, 1998. (Pubitemid 128434463)
16. H.-P. Schwefel. Evolution and Optimum Seeking. John Wiley, Chichester, UK, 1995.
17. H. Shimodaira. A diversity control-oriented-genetic algorithm (DCGA): performance in function optimization. In 2001 IEEE Congress on Evolutionary Computation, pages 44-51, Seoul, Korea, 2001. (Pubitemid 32806317)
18. R. E. Smith and D. E. Goldberg. Diploidy and dominance in artificial genetic search. Complex Systems, 6(3):251-285, 1992.
19. R. K. Ursem. Diversity-guided evolutionary algorithms. In Lecture Notes in Computer Science, pages 462-474. Springer, 2003.
20. R. Vencovsky and J. Crossa. Variance Effective Population Size under Mixed Self and Random Mating with Applications to Genetic Conservation of Species. Crop Science, 39(5):1282-1294, 1999. (Pubitemid 29461987)
21. J. Wang. Effective population size under random mating with a finite number of matings. Philosophical Transactions of the Royal Society - B, 360:1395-1409, 2005.
22. M. T. Wasan. Stochastic Approximation. Cambridge University Press, Cambridge, 1969.
23. S. Wright. Evolution in mendelian populations. Genetics, 16:97-159, 1931.
24. S. Yang. Non-stationary problems optimization using the primal-dual genetic algorithm. In Congr. Evol. Comput., pages 2246U-2253, 2003.
25. S. Yang and R. Tinós. A hybrid immigrants scheme for genetic algorithms in dynamic environments. International Journal of Automation and Computing, 4(3):243-254, 2007. (Pubitemid 47167351)