Abstract | ||
---|---|---|
Multiobjective optimization aims to simultaneously optimize two or more objectives for a problem, with multiobjective evolutionary algorithms (MOEAs) having become a popular research topic in evolutionary multiobjective optimization. We first define the multiobjective optimization problem and briefly summarize multiobjective optimization methods based on the evolutionary algorithm. Representative MOEAs from three categories are then introduced in detail, and we discuss some of the problems and challenges in improving MOEAs. Finally, future research directions for MOEAs are proposed. |
Year | DOI | Venue |
---|---|---|
2017 | 10.1109/CSE-EUC.2017.27 | 2017 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC) |
Keywords | DocType | Volume |
multobjective optimization,multobjective evolutionary algorithm,evolutionary multobjective optimization | Conference | 1 |
ISSN | ISBN | Citations |
1949-0828 | 978-1-5386-3222-2 | 2 |
PageRank | References | Authors |
0.36 | 22 | 2 |
Name | Order | Citations | PageRank |
---|---|---|---|
Jiawei Zhang | 1 | 806 | 72.17 |
Lining Xing | 2 | 16 | 8.51 |