Publications · 2003 · Conference paper
The Micro Genetic Algorithm 2: Towards Online Adaptation in Evolutionary Multiobjective Optimization
In Evolutionary Multi-Criterion Optimization. Second International Conference, EMO 2003, 2003
Abstract
In this paper, we deal with an important issue generally omitted in the current literature on evolutionary multiobjective optimization: on-line adaptation. We propose a revised version of our micro-GA for multiobjective optimization which does not require any parameter fine-tuning. Furthermore, we introduce in this paper a dynamic selection scheme through which our algorithm decides which is the “best’ crossover operator to be used at any given time. Such a scheme has helped to improve the performance of the new version of the algorithm which is called the micro-GA2 (μGA2). The new approach is validated using several test function and metrics taken from the specialized literature and it is compared to the NSGA-II and PAES.
BibTeX
@inproceedings{Toscano03,
author = {Gregorio {Toscano Pulido} and Carlos A. {Coello Coello}},
title = {The {M}icro {G}enetic {A}lgorithm 2: {T}owards {O}nline {A}daptation in {E}volutionary {M}ultiobjective {O}ptimization},
booktitle = {Evolutionary Multi-Criterion Optimization. Second International Conference, EMO 2003},
editor = {Carlos M. Fonseca and Peter J. Fleming and Eckart Zitzler and Kalyanmoy Deb and Lothar Thiele},
publisher = {Springer. Lecture Notes in Computer Science. Volume 2632},
pages = {252--266},
address = {Faro, Portugal},
month = {April},
year = {2003},
doi = {10.1007/3-540-36970-8_18},
url = {https://doi.org/10.1007/3-540-36970-8_18},
}