Pareto Dominance-Based Algorithms With Ranking Methods for Many-Objective Optimization
In Pareto dominance-based multi-objective evolutionary algorithms (PDMOEAs), Pareto dominance fails to provide the essential selection pressure required to drive the search toward convergence in many-objective optimization problems (MaOPs). Recently, the idea of using secondary criterion, such as kn...
Main Authors: | Vikas Palakonda, Rammohan Mallipeddi |
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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/7950899/ |
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