RT Journal Article
T1 A Study of the Combination of Variation Operators in the NSGA-II Algorithm
A1 Nebro-Urbaneja, Antonio Jesús
A1 Durillo, Juan J.
A1 Machín, Mirialys
A1 Coello Coello, Carlos A.
A1 Dorronsoro, Bernabé
K1 Computación evolutiva
AB Multi-objective evolutionary algorithms rely on the use of variation operators as their basic mechanism to carry out the evolutionaryprocess. These operators are usually fixed and applied in the same way during algorithm execution, e.g., the mutation probability in genetic algorithms. This paper analyses whether a more dynamic approach combining different operators with variable application rate along the search process allows to improve the static classical behavior. This way, we explorethe combined use of three different operators (simulated binary crossover, differential evolution’s operator, and polynomial mutation) inthe NSGA-II algorithm. We have considered two strategies for selecting the operators: random and adaptive. The resulting variants have beentested on a set of 19 complex problems, and our results indicate that bothschemes significantly improve the performance of the original NSGA-IIalgorithm, achieving the random and adaptive variants the best overallresults in the bi- and three-objective considered problems, respectively.
PB Springer
YR 2013
FD 2013
LK http://hdl.handle.net/10630/6746
UL http://hdl.handle.net/10630/6746
LA eng
NO UNIVERSIDAD DE MÁLAGA. CAMPUS DE EXCELENCIA INTERNACIONAL ANDALUCÍA TECH
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 3 mar 2026