Title :
Evolution strategies applied to perturbed objective functions
Author :
Bäck, Thomas ; Hammel, Ulrich
Author_Institution :
Dept. of Comput. Sci., Dortmund Univ., Germany
Abstract :
We investigate the behavior of evolution strategies on noisy objective functions. We show for the simple sphere model that convergence velocity is not reduced as long as the noise level is small compared to the function value. If the noise level reaches a certain threshold, a size of the parent population greater than 1 improves the convergence precision significantly. Convergence reliability is tested for two nonconvex functions. Again the search process seems to be not influenced by low level noise. Interpreting the impact of noise purely as a modification of the selection process gives new insight into the role of selection in evolution strategies
Keywords :
convergence of numerical methods; genetic algorithms; minimisation; noise; perturbation techniques; search problems; convergence precision; convergence reliability; convergence velocity; evolution strategies; function value; low level noise; noise level; noisy objective functions; nonconvex functions; parent population; perturbed objective functions; search process; simple sphere model; Application software; Computer science; Computer simulation; Convergence; Design optimization; Electronic switching systems; Genetic mutations; Noise level; Noise robustness; Testing;
Conference_Titel :
Evolutionary Computation, 1994. IEEE World Congress on Computational Intelligence., Proceedings of the First IEEE Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1899-4
DOI :
10.1109/ICEC.1994.350045
