Indicator-Based Constrained Multiobjective Evolutionary Algorithms

Solving constrained multiobjective optimization problems (CMOPs) is a challenging task since it is necessary to optimize several conflicting objective functions and handle various constraints simultaneously. A promising way to solve CMOPs is to integrate multiobjective evolutionary algorithms (MOEAs...

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Vydáno v:	IEEE transactions on systems, man, and cybernetics. Systems Ročník 51; číslo 9; s. 5414 - 5426
Hlavní autoři:	Liu, Zhi-Zhong, Wang, Yong, Wang, Bing-Chuan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	New York IEEE 01.09.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Automation Constrained multiobjective evolutionary algorithms (CMOEAs) constrained multiobjective optimization problems (CMOPs) constraint-handling technique Constraints Cybernetics Decision feedback equalizers Evolutionary algorithms Evolutionary computation Genetic algorithms Handling indicator Linear programming Multiple objective analysis Optimization Pareto optimization
ISSN:	2168-2216, 2168-2232
On-line přístup:	Získat plný text
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