Benchmarking Multi- and Many-Objective Evolutionary Algorithms Under Two Optimization Scenarios
Recently, a large number of multi-objective evolutionary algorithms (MOEAs) for many-objective optimization problems have been proposed in the evolutionary computation community. However, an exhaustive benchmarking study has never been performed. As a result, the performance of the MOEAs has not bee...
Main Authors: | Ryoji Tanabe, Hisao Ishibuchi, Akira Oyama |
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Format: | Article |
Language: | English |
Published: |
IEEE
2017-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8031325/ |
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