Abstract

Evolutionary multiobjective optimization has been a research area since the mid-1980s, and has experienced a very significant activity in the last 20 years. However, and in spite of the maturity of this field, there are still several important challenges lying ahead. This paper provides a short description of some of them, with a particular focus on open research areas, rather than on specific research topics or problems. The main aim of this paper is to motivate researchers and students to develop research in these areas, as this will contribute to maintaining this discipline active during the next few years.

Details

Title
Evolutionary multiobjective optimization: open research areas and some challenges lying ahead
Author
Coello Coello, Carlos A. 1   VIAFID ORCID Logo  ; González Brambila, Silvia 1 ; Figueroa Gamboa, Josué 1 ; Castillo Tapia, Ma Guadalupe 2 ; Hernández Gómez, Raquel 3 

1  UAM Azcapotzalco, Departamento de Sistemas, Mexico, Mexico (GRID:grid.7220.7) (ISNI:0000 0001 2157 0393) 
2  UAM Azcapotzalco, Departamento de Administración, Mexico, Mexico (GRID:grid.7220.7) (ISNI:0000 0001 2157 0393) 
3  CINVESTAV-IPN, Department of Computer Science (Evolutionary Computation Group), Mexico, Mexico (GRID:grid.512574.0) 
Pages
221-236
Publication year
2020
Publication date
Jul 2020
Publisher
Springer Nature B.V.
ISSN
21994536
e-ISSN
21986053
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1007/s40747-019-0113-4
ProQuest document ID
3098489234
Copyright
© The Author(s) 2019. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.