A dual-grid dual-phase strategy for constrained multi-objective optimization

Constrained multi-objective optimization problems (CMOPs) appear frequently in engineering applications. In some cases, feasible regions are narrow and/or disconnected. For this kind of problems, existing constraint-handling methods, integrated with multi-objective evolutionary algorithms, are easil...

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Bibliographic Details

Published in:	2019 IEEE Symposium Series on Computational Intelligence (SSCI) pp. 1881 - 1888
Main Authors:	Ming, Mengjun, Wang, Rui, Zhang, Tao, Ishibuchi, Hisao
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.12.2019
Subjects:	constrained multi-objective optimization problem (CMOP) Convergence dual-grid push and pull evolutionary algorithms Evolutionary computation MOEA/D-DPPS Pareto optimization Sociology Switches
Online Access:	Get full text
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