NSGA-II With Simple Modification Works Well on a Wide Variety of Many-Objective Problems
In the last two decades, the non-dominated sorting genetic algorithm II (NSGA-II) has been the most widely-used evolutionary multi-objective optimization (EMO) algorithm. However, its performance on a wide variety of many-objective test problems has not been examined in the literature. It has been i...
Main Authors: | Lie Meng Pang, Hisao Ishibuchi, Ke Shang |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/9229403/ |
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