Evolutionary algorithms and gradient search: Similarities and differences

IEEE Transactions on Evolutionary Computation

Volumn 2, Issue 2, 1998, Pages 45-55

  Salomon, Ralf ^a  

^a UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Evolution strategies; Evolutionary algorithms; Gradient search; Optimization

Indexed keywords

COMPUTER SIMULATION; CONVERGENCE OF NUMERICAL METHODS; FUNCTIONS; GENETIC ALGORITHMS; HEURISTIC METHODS; OPTIMIZATION; VECTORS;

EVOLUTIONARY ALGORITHMS; EVOLUTIONARY GRADIENT SEARCH METHOD;

COMPUTATIONAL METHODS;

EID: 0032108106     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/4235.728207     Document Type: Article

References (25)

1. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C. Cambridge, U.K.: Cambridge Univ. Press, 1994.
2. D. G. Luenberger, Linear and Nonlinear Programming. Reading, MA: Addison-Wesley, 1984.
3. K. A. De Jong, An analysis of the behavior of a class of genetic adaptive systems, Ph.D. dissertation, Univ. of Michigan, Ann Arbor, 1975.
4. D. E. Goldberg, Genetic Algorithms in Search, Optimization and Machine Learning. Reading, MA: Addison-Wesley, 1989.
5. J. H. Holland, Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, 2nd ed. Cambridge, MA: MIT Press, 1992.
6. L. J. Fogel, Autonomous automata, Indust. Res., vol. 4, pp. 14-19, 1962.
7. D. B. Fogel, Evolutionary Computation: Toward a New Philosophy of Machine Learning Intelligence. Piscataway, NJ: IEEE Press, 1995.
8. I. Rechenberg, Evolutionsstrategie. Stuttgart, Germany: FrommannHolzboog, 1973.
9. _, Evolutionsstrategie'94. Stuttgart: Frommann-Holzboog, 1994.
10. H.-P. Schwefel, Evolution and Optimum Seeking. New York: Wiley, Inc., 1995.
11. T. Back and H.-P. Schwefel, An overview of evolutionary algorithms for parameter optimization, Evol. Comput., vol. 1, no. 1, pp. 1-23, 1993.
12. D. Thierens and D. Goldberg, Convergence models of genetic algorithm selection schemes, in Proc. Parallel Problem Solving from Nature 3, Y. Davidor, H. P. Schwefel, and R. Männer, Eds. Berlin, Germany: Springer-Verlag, 1994, pp. 119-129.
13. H.-P. Schwefel, Evolutionary Computation-A study on collective learning, in Proc. World Multiconference Systetnics, Cybernetics and Informatics (SCI'97), N. Callaos, C. M. Khoong, and E. Cohen, Eds. Orlando, FL: International Institute of Informatics and Systetnics (HIS), 1997, vol. 2, pp. 198-205.
14. N. Hansen and A. Ostermeier, Convergence properties of evolution strategies with the derandomized covariance matrix adaptation: The (//////, A)-CMA-ES, in Proc. 5th Cong. Intelligent Techniques and Soft Computing EUFIT'97, H.-J. Zimmermann, Ed. Aachen, Germany: Verlag Mainz, 1997, pp. 650-654.
15. H.-M. Voigt and H. Mühlenbein, Gene pool recombination and the utilization of covariances for the breeder genetic algorithm, in Proc. 2nd IEEE Int. Conf. Evolutionary Computation. Piscataway, NJ: IEEE Press, 1995, pp. 172-177.
16. T. Back and F. Kursawe, Evolutionary algorithms for fuzzy logic: A brief overview, in Fuzzy Logic and Soft Computing, B. BouchonMeunier, R. R. Yager, and L. A. Zadeh, Eds. Singapore: World Scientific, 1995, vol. 4, pp. 3-10.
17. H.-G. Beyer, On the 'explorative' power of ES/EP-like algorithms, in Proc. 7th Annual Conf. Evolutionary Programming EP'98, V. W. Porto, N. Saravanan, D. E. Waagen, and A. E. Eiben, Eds. Berlin, Germany: Springer-Verlag, 1998.
18. H. Mühlenbein and D. Schlierkamp-Voosen, Predictive models for the breeder genetic algorithm I, Evol. Comput., vol. 1, no. 1, pp. 25-50, 1993.
19. H.-G. Beyer, An alternative explanation for the manner in which genetic algorithms operate, BioSystems, vol. 41, pp. 1-15, 1997.
20. D. Rumelhart et al. Ed., Parallel Distributed Processing: Explorations in the Microstructure of Cognition (Psychological and Biological Models) vol. 2. Cambridge, MA: MIT Press, 1986.
21. R. Salomon and J. L. van Hemmen, Accelerating backpropagation through dynamic self-adaptation, Neural Networks, vol. 9, no. 4, pp. 589-601, 1996.
22. H. H. Rosenbrock, An automatic method for finding the greatest or least value of a function, Comput. J., vol. 3, pp. 175-184, 1960.
23. R. Salomon, Reevaluating genetic algorithm performance under coordinate rotation of benchmark functions, BioSystems, vol. 39, no. 3, pp. 263-278, 1996.
24. N. Saravanan, D. B. Fogel, and K. M. Nelson, A comparison of methods for self-adaptation in evolutionary algorithms, BioSystems, vol. 36, pp. 157-166, 1995.
25. R. Salomon, Accelerating the evolutionary-gradient-search procedure: Individual step sizes, in Proc. 5th Int. Conf. Parallel Problem Solving from Nature (PPSN V). Berlin, Germany: Springer-Verlag, 1998.