A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization
Due to increased search complexity in multi-objective optimization, premature convergence becomes a problem. Complex engineering problems poses high number of variables with many constraints. Hence, more difficult benchmark problems must be utilized to validate new algorithms performance. A well-kno...
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Main Authors: | , , , , |
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Format: | Article |
Published: |
Elsevier
2018
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Online Access: | http://eprints.um.edu.my/21228/ https://doi.org/10.1016/j.asoc.2018.06.022 |
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