Publications · 2016 · Journal article
A Review of Surrogate Assisted Multiobjective Evolutionary Algorithms
Computational Intelligence and Neuroscience, 2016, 2016
Abstract
Multiobjective evolutionary algorithms have incorporated surrogate models in order to reduce the number of required evaluations to approximate the Pareto front of computationally expensive multiobjective optimization problems. Currently, few works have reviewed the state of the art in this topic. However, the existing reviews have focused on classifying the evolutionary multiobjective optimization algorithms with respect to the type of underlying surrogate model. In this paper, we center our focus on classifying multiobjective evolutionary algorithms with respect to their integration with surrogate models. This interaction has led us to classify similar approaches and identify advantages and disadvantages of each class.
BibTeX
@article{Diaz-Manriquez16a,
author = {Díaz-Manríquez, Alan and Toscano, Gregorio and Barron-Zambrano, {Jose Hugo} and Tello-Leal, Edgar},
title = {A Review of Surrogate Assisted Multiobjective Evolutionary Algorithms},
journal = {Computational Intelligence and Neuroscience},
month = {May},
year = {2016},
volume = {2016},
note = {article ID 9420460},
doi = {10.1155/2016/9420460},
url = {http://dx.doi.org/10.1155/2016/9420460}
}