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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Bibliographic Details
Main Authors: Mohd Zain, Mohamad Zihin, Kanesan, Jeevan, Chuah, Joon Huang, Dhanapal, Saroja, Kendall, Graham
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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