%0 Report %1 DebB_99_sel %A Deb, K. %A Beyer, H. %C Germany %D 1999 %K imported %N CI-61/99 %T Self-Adaptive: Genetic Algorithms with Simulated Binary Crossover %U citeseer.ist.psu.edu/deb99selfadaptive.html %X Self-adaptation is an essential feature of natural evolution. However, in the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored only with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the selfadaptive feature of real-parameter genetic algorithms (GAs) using simulated binary crossover (SBX) operator and without any mutation operator. The connection between the working of self-adaptive ESs and real-parameter GAs with SBX operator is also discussed. Thereafter, the self-adaptive behavior of real-parameter GAs is demonstrated on a number of test problems commonly-used in the ES literature. The remarkable similarity in the working principle of real-parameter GAs and self-adaptive ESs shown in this study suggests the need of emphasizing further studies on self-adaptive GAs

@techreport{DebB_99_sel, abstract = {Self-adaptation is an essential feature of natural evolution. However, in the context of function optimization, self-adaptation features of evolutionary search algorithms have been explored only with evolution strategy (ES) and evolutionary programming (EP). In this paper, we demonstrate the selfadaptive feature of real-parameter genetic algorithms (GAs) using simulated binary crossover (SBX) operator and without any mutation operator. The connection between the working of self-adaptive ESs and real-parameter GAs with SBX operator is also discussed. Thereafter, the self-adaptive behavior of real-parameter GAs is demonstrated on a number of test problems commonly-used in the ES literature. The remarkable similarity in the working principle of real-parameter GAs and self-adaptive ESs shown in this study suggests the need of emphasizing further studies on self-adaptive GAs}, added-at = {2008-06-26T18:58:40.000+0200}, address = {Germany}, author = {Deb, K. and Beyer, H.}, biburl = {https://www.bibsonomy.org/bibtex/21a58a8ef792b9c990b9572260f48e8c9/jacquenot}, folder = {Theory/Optimization_methods/Evolutionary_Algorithms/Genetic_Algorithms}, institution = {Department of Computer Science, University of Dortmund}, interhash = {8d509685185b80b4506d2d5518f552ff}, intrahash = {1a58a8ef792b9c990b9572260f48e8c9}, keywords = {imported}, month = {March}, number = {CI-61/99}, owner = {jacquenot}, text = {K. Deb and H.-G. Beyer. Self-adaptive Genetic Algorithms with Simulated Binary Crossover. Technical report no. CI-61/99, University of Dortmund, Department of Computer Science/LS11, 1999.}, timestamp = {2008-06-26T18:58:41.000+0200}, title = {{S}elf-{A}daptive: {G}enetic {A}lgorithms with {S}imulated {B}inary {C}rossover}, url = {citeseer.ist.psu.edu/deb99selfadaptive.html}, year = 1999 }