Going for the big fishes: Discovering and combining large neutral and massively multimodal building-blocks with model based macro-mutation

GECCO'08: Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation 2008

Volumn , Issue , 2008, Pages 423-430

  Iclǎnzan, David ^a   Dumitrescu, D ^a  

^a BABE BOLYAI UNIVERSITY   (Romania)

Author keywords

Adaptive neighborhood structure; Macro mutation; Model based local search; Scalability

Indexed keywords

EVOLUTIONARY ALGORITHMS; LOCAL SEARCH (OPTIMIZATION); MODEL BUILDINGS; SCALABILITY;

ADAPTIVE NEIGHBORHOOD STRUCTURE; BUILDING BLOCKES; MACRO MUTATIONS; META HEURISTICS; MODEL BASED LOCAL-SEARCH; NUMBER OF SAMPLES; POPULATION SIZING; PROBABILISTIC MODELING;

PROBLEM SOLVING;

EID: 57349179930     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (23)

1. E. D. de Jong, R. A. Watson, and D. Thierens. On the complexity of hierarchical problem solving. In H.-G. Beyer and U.-M. O'Reilly, editors, GECCO '05, pages 1201-1208. ACM, june 2005.
2. D. E. Goldberg. The Design of Innovation: Lessons from and for Competent Genetic Algorithms. Kluwer Academic Publishers, Norwell, MA, USA, 2002.
3. D. E. Goldberg, K. Deb, and J. Horn. Massive multimodality, deception, and genetic algorithms. In R. Männer and B. Manderick, editors, Parallel Problem Solving from Nature, 2, Amsterdam, 1992. Elsevier Science Publishers, B. V.
4. D. E. Goldberg, K. Sastry, and T. Latoza. On the supply of building blocks. In L. Spector, E. D. Goodman, A. Wu, W. B. Langdon, H.-M. Voigt, M. Gen, S. Sen, M. Dorigo, S. Pezeshk, M. H. Garzon, and E. Burke, editors, Proceedings of the Genetic and Evolutionary Computation Conference (GECCO-2001), pages 336-342, San Francisco, California, USA, 7-11 July 2001. Morgan Kaufmann.
5. 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.
6. J. Jiang. Image compression with neural networks: A survey. SP:IC, 14(9):737-760, July 1999.
7. T. Jones. Evolutionary Algorithms, Fitness Landscapes and Search. PhD thesis, University of New Mexico, Albuquerque, NM, 1995.
8. T. Kohonen. Self-organized formation of topologically correct feature maps. Biological Cybernetics, 43:59-69, 1982.
9. Z. Li and E. D. Goodman. Learning building block structure from crossover failure. In GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation, pages 1280-1287, New York, NY, USA, 2007. ACM.
10. C. F. Lima, K. Sastry, D. E. Goldberg, and F. G. Lobo. Combining competent crossover and mutation operators: a probabilistic model building approach. In GECCO '05, pages 735-742, NY, USA, 2005. ACM.
11. S. W. Mahfoud. Niching methods for genetic algorithms. PhD thesis, Dept. General Engineering, University of Illinois, Urbana, Illinois, 1995. Also, IlliGAL Report No. 95001.
12. 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, Proc. of the First European Conference on Artificial Life, pages 245-254, Cambridge, MA, 1992. MIT Press.
13. M. Mitchell and J. H. Holland. When will a genetic algorithm outperform hill climbing? In S. Forrest, editor, Proceedings of the 5th International Conference on Genetic Algorithms, pages 647-647, San Mateo, CA, USA, July 1993. Morgan Kaufmann.
14. M. Pelikan and D. E. Goldberg. Escaping hierarchical traps with competent genetic algorithms. In L. S. et al, editor, GECCO '01:, pages 511-518, San Francisco, California, USA, 7-11 2001. Morgan Kaufmann.
15. M. Pelikan, D. E. Goldberg, and E. Cantú-Paz. Linkage problem, distribution estimation, and bayesian networks. Evolutionary Computation, 8(3):311-340, 2000.
16. M. Pelikan, K. Sastry, and D. E. Goldberg. Scalability of the bayesian optimization algorithm. Int. J. Approx. Reasoning, 31(3):221-258, 2002.
17. K. Sastry and D. E. Goldberg. Designing competent mutation operators via probabilistic model building of neighborhoods. In GECCO '04, pages 114-125. Springer, LNCS, vol. 3103, June 26-30, 2004.
18. K. Sastry and D. E. Goldberg. Let's get ready to rumble: Crossover versus mutation head to head. In GECCO '04, pages 126-137. Springer, LNCS, vol. 3103, June 2004.
19. D. Thierens. Scalability problems of simple genetic algorithms. Evolutionary Computation, 7(4):331-352, 1999.
20. R. A. Watson, G. Hornby, and J. B. Pollack. Modeling building-block interdependency. In Proc. of PPSN V, pages 97-108, London, UK, 1998. Springer, LNCS.
21. R. A. Watson and J. B. Pollack. Hierarchically consistent test problems for genetic algorithms: Summary and additional results. In S. Brave, editor, GECCO '99: Late Breaking Papers, pages 292-297, Orlando, Florida, USA, 13 July 1999.
22. A. Yassine, D. Falkenburg, and K. Chelst. Engineering design management: an information structure approach. International Journal of Production Research, 37(13):2957-2975, 1999.
23. T.-L. Yu and D. E. Goldberg. Conquering hierarchical difficulty by explicit chunking: substructural chromosome compression. In GECCO '06:, pages 1385-1392, NY, USA, 2006. ACM Press.