A Survey of Multiobjective Evolutionary Algorithms Based on Decomposition: Variants, Challenges and Future Directions
There are many challengeable multiobjective optimization problems in different areas, whose optimization objectives are usually diversionary. Decomposition methods and evolution mechanisms enable multiobjective evolutionary algorithms based on decomposition (MOEA/D) to tackle these complex optimizat...
Main Authors: | Qian Xu, Zhanqi Xu, Tao Ma |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
|
Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8998284/ |
Similar Items
-
Objective reduction in many-objective optimization : evolutionary multiobjective approaches and comprehensive analysis
by: Yuan, Yuan, et al.
Published: (2020) -
A Survey of Decomposition Based Evolutionary Algorithms for Many-Objective Optimization Problems
by: Xiaofang Guo
Published: (2022-01-01) -
A many-objective evolutionary algorithm with metric-based reference vector adjustment
by: Xujian Wang, et al.
Published: (2023-07-01) -
Development of a Bio-inspired Hybrid Decomposition Algorithm Based on Whale and Differential Evolution Strategies for Multiobjective Optimization
by: André O. Martins, et al.
Published: (2023-06-01) -
Preference-Based Evolutionary Multiobjective Optimization Through the Use of Reservation and Aspiration Points
by: Sandra Gonzalez-Gallardo, et al.
Published: (2021-01-01)