RT Journal Article
T1 Evolver: Meta-optimizing multi-objective metaheuristics.
A1 Aldana Martín, José Francisco
A1 Durillo, Juan J.
A1 Nebro-Urbaneja, Antonio Jesús
K1 Optimización matemática
K1 Programación heurística
AB Evolver is a tool based on the formulation of the automatic configuration and design of multi-objective metaheuristics as a multi-objective optimization problem that can be solved by using the same kind of algorithms; i.e., we are applying a meta-optimization approach. Evolver provides highly configurable implementations of representative multi-objective solvers which can be automatically configured from a number of multi-objective problems used as the training set and a list of quality indicators which are the objectives to be optimized. Our tool is based on the jMetal framework, so a large number of existing algorithms can be used as meta-optimizers.A graphical user interface allows scientists to easily define auto-configuration scenarios, thus simplifying thecomplex process of finding high-quality algorithm settings.
PB Elsevier
YR 2023
FD 2023-10-10
LK https://hdl.handle.net/10630/28010
UL https://hdl.handle.net/10630/28010
LA eng
NO Aldana-Martín, J. F., Durillo, J. J., & Nebro, A. J. (2023). Evolver: Meta-optimizing multi-objective metaheuristics. SoftwareX, 24, 101551. https://doi.org/10.1016/j.softx.2023.101551
NO Partial funding for open access: Universidad de Málaga / CBUA
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 3 mar 2026