Objective reduction in many-objective optimization : evolutionary multiobjective approaches and comprehensive analysis
Many-objective optimization problems bring great difficulties to the existing multiobjective evolutionary algorithms, in terms of selection operators, computational cost, visualization of the high-dimensional tradeoff front, and so on. Objective reduction can alleviate such difficulties by removing...
Saved in:
Main Authors: | Yuan, Yuan, Ong, Yew-Soon, Gupta, Abhishek, Xu, Hua |
---|---|
Other Authors: | School of Computer Science and Engineering |
Format: | Article |
Language: | English |
Published: |
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/140635 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Multiobjective evolutionary algorithm with controllable focus on the knees of the pareto front
by: Rachmawati, L., et al.
Published: (2014) -
A multiobjective evolutionary algorithm toolbox for computer-aided multiobjective optimization
by: Tan, K.C., et al.
Published: (2014) -
Incorporating the notion of relative importance of objectives in evolutionary multiobjective optimization
by: Rachmawati, L., et al.
Published: (2014) -
Comparison between MOEA/D and NSGA-III on a set of many and multi-objective benchmark problems with challenging difficulties
by: Li, Hui, et al.
Published: (2021) -
An investigation on evolutionary gradient search for multi-objective optimization
by: Goh, C.K., et al.
Published: (2014)