Multipopulation Evolution-Based Dynamic Constrained Multiobjective Optimization Under Diverse Changing Environments

Dynamic constrained multiobjective optimization involves irregular changes in the distribution of the true Pareto-optimal fronts, drastic changes in the feasible region caused by constraints, and the movement directions and magnitudes of the optimal distance variables due to diverse changing environ...

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Bibliographic Details
Published in:	IEEE transactions on evolutionary computation Vol. 28; no. 3; pp. 763 - 777
Main Authors:	Chen, Qingda, Ding, Jinliang, Yen, Gary G., Yang, Shengxiang, Chai, Tianyou
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.06.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithm design and analysis Algorithms Changing environments Constraint handling Constraints Dynamic constrained multiobjective optimization Dynamic response Evolution Feasibility Generators Multiple objective analysis Optimization Pareto optimization Pareto optimum population selection Real variables Strategy Tracking tribe classification operator
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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