caa a22 4500 44587810X CHVBK 20180317145533.0 cr unu---uuuuu 170323e20110301xx s 000 0 eng 10.1007/s11081-010-9114-2 doi (NATIONALLICENCE)springer-10.1007/s11081-010-9114-2 An adaptive constraint handling technique fordifferential evolution with dynamic use of variants inengineering optimization [Elektronische Daten] [Eduardo daSilva, Helio Barbosa, Afonso Lemonge] Differential Evolution is a simple and efficient stochastic population-based heuristics for global optimization over continuous spaces. As with other nature inspired techniques, there is no provision for constraint handling in its original formulation, and a few possibilities have been proposed in the literature. In this paper an adaptive penalty technique (APM), which has been shown to be quite effective within genetic algorithms, is adopted for constraint handling within differential evolution. The technique, which requires no extra parameters, is based on feedback obtained from the current status of the population of candidate solutions, and automatically defines, for each constraint, its corresponding penalty coefficient. Equality as well as inequality constraints can be dealt with. In this paper we additionally introduce a mechanism for dynamically selecting the mutation operator, according to its performance, among several variants commonly used in the literature. In order to assess the applicability and performance of the proposed procedure, several test-problems from the structural and mechanical engineering optimization literature are considered. Springer Science+Business Media, LLC, 2010 Differential evolution nationallicence Constrained optimization nationallicence Adaptive penalty nationallicence daSilva Eduardo Laboratório Nacional de Computação Científica—LNCC, Petrópolis, RJ, Brasil aut Barbosa Helio Laboratório Nacional de Computação Científica—LNCC, Petrópolis, RJ, Brasil aut Lemonge Afonso Departamento de Mecânica Aplicada e Computacional, Faculdade de Engenharia, Universidade Federal de Juiz de Fora, Juiz de Fora, MG, Brasil aut Optimization and Engineering Springer US; http://www.springer-ny.com 12/1-2(2011-03-01), 31-54 1389-4420 12:1-2<31 2011 12 11081 https://doi.org/10.1007/s11081-010-9114-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11081-010-9114-2 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- daSilva Eduardo Laboratório Nacional de Computação Científica—LNCC, Petrópolis, RJ, Brasil aut NATIONALLICENCE 700 1- Barbosa Helio Laboratório Nacional de Computação Científica—LNCC, Petrópolis, RJ, Brasil aut NATIONALLICENCE 700 1- Lemonge Afonso Departamento de Mecânica Aplicada e Computacional, Faculdade de Engenharia, Universidade Federal de Juiz de Fora, Juiz de Fora, MG, Brasil aut NATIONALLICENCE 773 0- Optimization and Engineering Springer US; http://www.springer-ny.com 12/1-2(2011-03-01), 31-54 1389-4420 12:1-2<31 2011 12 11081 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer