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...

Full description

Saved in:

Bibliographic Details
Published in:	IEEE transactions on systems, man, and cybernetics. Systems Vol. 51; no. 9; pp. 5414 - 5426
Main Authors:	Liu, Zhi-Zhong, Wang, Yong, Wang, Bing-Chuan
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.09.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	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
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!

Be the first to leave a comment!