RT Conference Proceedings
T1 A Study About Meta-Optimizing the NSGA-II Multi-Objective Evolutionary Algorithm.
A1 Aldana Martín, José Francisco
A1 Nebro-Urbaneja, Antonio Jesús
A1 Durillo, Juan J.
A1 Roldán-García, María del Mar
K1 Programación heurística
K1 Optimización matemática
K1 Algoritmos computacionales
AB The automatic design of multi-objective metaheuristics is an active research line aimed at, given a set of problems used as training set, to find the configuration of a multi-objective optimizer able of solving them efficiently. The expected outcome is that the auto-configured algorithm can be used of find accurate Pareto front approximations for other problems. In this paper, we conduct a study on the meta-optimization of the wellknown NSGA-II algorithm, i.e., we intend to use NSGA-II as an automatic configuration tool to find configurations of NSGA-II. This search can be formulated as a multi-objective problem where the decision variables are the NSGA-II components and parameters and the the objectives are quality indicators that have to be minimized. To develop this study, we rely on the jMetal framework. The analysis we propose is aimed at answering the following research questions: RQ1 - how complex is to build the meta-optimization package?, and RQ2 - can accurate configurations be found? We conduct an experimentation to give an answer to these questions.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/27974
UL https://hdl.handle.net/10630/27974
LA spa
NO Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 3 mar 2026