Comparing a coevolutionary genetic algorithm for multiobjective optimization

Proceedings of the 2002 Congress on Evolutionary Computation, CEC 2002

Volumn 2, Issue , 2002, Pages 1157-1162

  Lohn, Jason D ^a,c   Kraus, William F ^b,c   Haith, Gary L ^d  

^a Computational Sciences Division ^*  (United States)

^b QSS GROUP INC   (United States)

^c NASA AMES RESEARCH CENTER   (United States)

^d NAREX Inc   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; GENETIC ALGORITHMS; PARETO PRINCIPLE;

COEVOLUTIONARY GENETIC ALGORITHM; COMPETITIVE CO EVOLUTIONS; FINDING SOLUTIONS; FITNESS CALCULATION; PARETO FRONT; PARETO-OPTIMAL FRONT; TEST FUNCTIONS; THEORY OF LEARNING;

MULTIOBJECTIVE OPTIMIZATION;

EID: 33749864685     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2002.1004406     Document Type: Conference Paper

References (17)

1. K. Dejong, M. Potter, Evolving Complex Structures via Cooperative Coevolution. Proc. Fourth Annual Conf. on Evolutionary Programming MIT Press, pp. 307-317, 1995.
2. S. G. Ficici, Challenges in coevolutionary learning: Arms-race dynamics, open-endedness, and mediocre stable states, 1995.
3. G. L. Haith, S. P. Colombano, J. D. Lohn, D. Stassinopoulos, "Coevolution for Problem Simplification," Proc. 1999 Genetic and Evolutionary Computation Conference, 1999.
4. D. W. Hillis, Co-evolving parasites improve simulated evolution as an optimization procedure. Pages 313-324 of: Langton, C., Taylor, C., Farmer, J. D., Rasmussen, S. (eds), Artificial life 2, vol. X. Redwood City, CA: AddisonWesley, 1991.
5. H. Juille, J. Pollack, "Coevolving the "ideal" trainer: Application to the discovery of cellular automata rules," Proc. Third Annual Genetic Programming Conf., 1998.
6. J. D. Lohn, G. L. Haith, S. P. Colombano, D. Stassinopoulos, "A Comparison of Dynamic Fitness Schedules for Evolutionary Design of Amplifiers," Proc. of the First NASA/DoD Workshop on Evolvable Hardware, Pasadena, CA, IEEE Computer Society Press, 1999, pp. 87-92.
7. J. D. Lohn, W. F. Kraus, D. S. Linden, S. P. Colombano, "Evelutionary Optimization of Yagi-Uda Antennas," Proc. of the Fourth International Conference on Evolvable Systems, Y. Liu, K. Tanaka, M. Iwata, T. Higuchi, M. Yasunaga (Eds. ), Tokyo, October 3-5, 2001, Springer-Verlag, pp. 236-243.
8. J. Paredis, Coevolutionary constraint satisfaction. Pages 46-55 of: Proceedings of the third international conference on parallel problem solving from nature, vol. 866. Springer-Verlag, 1994.
9. J. Paredis, Steps towards co-evolutionary classification neural networks. Pages 102-108 of: Brooks, R., Mass, P. (eds), Artificial Life IV. Cambridge, MA: MIT Press, 1994.
10. J. Paredis, The symbiotic evolution of solutions and their representations. Pages 359-365 of: Eshelman, L. (ed), Proceedings of the sixth international conference on genetic algorithms. San Mateo, CA: Morgan Kaufmann, 1995.
11. J. Paredis, The handbook of evolutionary computation. Oxford University Press. Chap. Coevolutionary Algorithms, 1998.
12. J. Pollack, A. Blair, M. Land, "Coevolution of a backgammon player," Proc. of Artificial Life 5, Langton, C. (ed), MIT Press, 1996.
13. C. D. Rosin, R. K. Belew, New Methods for Competitive Coevolution, Tech. Rapt. C596-491, Department of Computer Science and Engineering, University of California, San Diego, 1996.
14. C. D. Rosin, "Coevolutionary Search Among Adversaries," Ph. D. Thesis, University of California, San Diego, 1997.
15. D. Van Veldhuizen, "Multiobjective Evolutionary Algorithms: Classifications, Anal.yses, and New Innovations," Ph. D. Thesis, Air Force Institute of Technology, 1999.
16. E. Zitzler, L. Thiele, "Multiobjective Optimization using Evelutionary Algorithms-A Comparitive Case Study," Parallel Problem Solving &om Nature V, pp. 292-301, Springer, 1998.
17. E. Zitzler, K. Deb, and L. Thiele, "Comparison of Multiobjective Evolutionary Algorithms: Empirical Results," Evolutionary Computation, 8(2), pp. 173-195, Summer 2000.