English

Push and Pull Search Embedded in an M2M Framework for Solving Constrained Multi-objective Optimization Problems

Neural and Evolutionary Computing 2019-06-04 v1
Authors: Zhun Fan , Zhaojun Wang , Wenji Li , Yutong Yuan , Yugen You , Zhi Yang , Fuzan Sun , Jie Ruan , Zhaocheng Li
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Abstract

In dealing with constrained multi-objective optimization problems (CMOPs), a key issue of multi-objective evolutionary algorithms (MOEAs) is to balance the convergence and diversity of working populations.

Keywords

multi-objective optimization evolutionary algorithm optimization algorithm

Cite

@article{arxiv.1906.00402,
  title  = {Push and Pull Search Embedded in an M2M Framework for Solving Constrained Multi-objective Optimization Problems},
  author = {Zhun Fan and Zhaojun Wang and Wenji Li and Yutong Yuan and Yugen You and Zhi Yang and Fuzan Sun and Jie Ruan and Zhaocheng Li},
  journal= {arXiv preprint arXiv:1906.00402},
  year   = {2019}
}

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