Automatically Designing State-of-the-Art Multi- and Many-Objective Evolutionary Algorithms

A recent comparison of well-established multiobjective evolutionary algorithms (MOEAs) has helped better identify the current state-of-the-art by considering (i) parameter tuning through automatic configuration, (ii) a wide range of different setups, and (iii) various performance metrics. Here, we a...

Full description

Bibliographic Details

Published in:	Evolutionary computation Vol. 28; no. 2; p. 195
Main Authors:	Bezerra, Leonardo C T, López-Ibáñez, Manuel, Stützle, Thomas
Format:	Journal Article
Language:	English
Published:	United States 01.06.2020
Subjects:	Algorithms Automation Biological Evolution automatic algorithm design Multiobjective optimization evolutionary algorithms
ISSN:	1530-9304, 1530-9304
Online Access:	Get more information
Tags:	Add Tag No Tags, Be the first to tag this record!