Robust and Efficient Genetic Algorithms with Hierarchical Niching and a Sustainable Evolutionary Computation Model

1. Goldberg, D.E.: Sizing Populations for Serial and Parallel Genetic Algorithms. In: Schaffer, J.D. (ed.) Proceedings of the Third International Conference on Genetic Algorithms, Kaufmann, San Mateo (1989)

   Google Scholar 

2. Harik, G.R., Lobo, F.G.: A parameter-less genetic algorithm. In: Proceedings of the Genetic and Evolutionary Computation Conference (1999)

   Google Scholar 

3. Mahfoud, S.W.: Niching Methods for Genetic Algorithms, Ph.D. Thesis, University of Illinois at Urbana-Champaign (1995)

   Google Scholar 

4. Hu, J., Goodman, E.D.: Hierarchical Fair Competition Model for Parallel Evolutionary Algorithms. In: Proceedings, Congress on Evolutionary Computation, CEC 2002, IEEE World Congress on Computational Intelligence, Honolulu, Hawaii, May 2002, IEEE Computer Society Press, Los Alamitos (2002)

   Google Scholar 

5. Hu, J., Goodman, E.D., Seo, K.: Continuous Hierarchical Fair Competition Model for Sustainable Innovation in Genetic Programming. In: Genetic Programming Theory and Practice, pp. 81–98. Kluwer Academic Publishers, Dordrecht (2003)

   Google Scholar 

6. Holland, J.H.: Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor (1975)

   Google Scholar 

7. De Jong, K.A.: An analysis of the behavior of a class of genetic adaptive systems (Doctoral dissertation, University of Michigan). Dissertation Abstracts International, 36(10),514B (University Microfilms No. 76-9381) (1975)

   Google Scholar 

8. Mahfoud, S.W.: Crowding and preselection revisited. In: Proc. Parallel problem Solving from Nature, PPSN 1992, Brussels (1992)

   Google Scholar 

9. Goldberg, D.E., Richardson, J.: Genetic algorithms with sharing for multimodal function optimization. In: Grefenstette, J.J. (ed.) Proceedings of the 2nd International Conference on Genetic Algorithms, pp. 41–49. Lawrence Erlbaum, Hillsdale (1987)

   Google Scholar 

10. Beasley, D., Bull, D.R., Martin, R.R.: A sequential niche technique for multimodal function optimization. Evolutionary Computation 1(2), 101–125 (1993)

    Article  Google Scholar 

11. Harik, G.: Finding multimodal solutions using restricted tournament selection. In: Proceedings of Sixth International Conference on Genetic Algorithms (1995)

    Google Scholar 

12. Darwen, P., Yao, X.: Every niching method has its niche: Fitness sharing and implicit sharing compared. In: Voigt, H.-M., Ebeling, W., Rechenberg, I., Schwefel, H.-P. (eds.) Parallel Problem Solving from Nature– PPSN IV, pp. 398–407. Springer, Berlin (1996)

    Chapter  Google Scholar 

13. Mahfoud, S.M.: A Comparison of Parallel and Sequential Niching Methods. In: Proceedings of Genetic and Evolutionary Computation Conference, pp. 136–143 (1995)

    Google Scholar 

14. Sareni, B., Krahenbuhl, L.: Fitness Sharing and Niching Methods revisited. IEEE Trans. on Evolutionary Computation 2(3), 97–106 (1998)

    Article  Google Scholar 

15. Ursem, R.K.: When Sharing Fails. In: Proceedings of the Third Congress on Evolutionary Computation, CEC 2001 (2001)

    Google Scholar 

16. Hutter, M.: Fitness Uniform Selection to Preserve Genetic Diversity. In: Proceedings of the 2002 Congress on Evolutionary (CEC 2002), Hawaii, pp. 783–788 (2002)

    Google Scholar 

17. Buckling, A., et al.: Adaptation limits diversification of experimental bacterial populations. Science 302, 2107–2109 (2003)

    Article  Google Scholar 

18. Hu, J., Goodman, E.D., Seo, K., Fan, Z., Rosenberg, R.C.: HFC: a Continuing EA Framework for Scalable Evolutionary Synthesis. In: Proceedings of the 2003 AAAI Spring Symposium - Computational Synthesis: From Basic Building Blocks to High Level Functionality, Stanford, California, March, 24-26, pp. 106–113 (2003)

    Google Scholar 

19. Pelikan, M., Goldberg, D.E., Cantú-Paz, E.E.: BOA: The Bayesian optimization algorithm. In: Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 1999), vol. I, pp. 525–532 (1999)

    Google Scholar 

20. Watson, R.: Analysis of recombinative algorithms on a nonseparable building block problem. In: Martin, W., Spears, W. (eds.) Foundations of Genetic Algorithms 6, pp. 69–89. Morgan Kaufmann, San Mateo (2001)

    Chapter  Google Scholar 

21. Hu, J., Goodman, E., Seo, K., Fan, Z., Rosenberg, R.: The Hierarchical Fair Competition (HFC) Framework for Sustainable Evolutionary Algorithms. Evolutionary Computation 13(1) (2005) (to appear)

    Google Scholar 

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