Hyper multi-objective evolutionary algorithm for multi-objective optimization problems

Multi-objective optimization problems (MOPs) are very common in practice. To solve MOPs, many kinds of multi-objective evolutionary algorithms (MOEAs) are proposed. However, different MOEAs have different performances for different MOPs. Therefore, it is a time-consuming task to choose a suitable MO...

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Bibliographic Details
Published in:	Soft computing (Berlin, Germany) Vol. 21; no. 20; pp. 5883 - 5891
Main Authors:	Guo, Weian, Chen, Ming, Wang, Lei, Wu, Qidi
Format:	Journal Article
Language:	English
Published:	Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2017 Springer Nature B.V
Subjects:	Artificial Intelligence Computational Intelligence Control Decomposition Engineering Evolutionary algorithms Focus Genetic algorithms Mathematical Logic and Foundations Mechatronics Multiple objective analysis Objectives Optimization Robotics Group Multi-objective optimization problems Coverage rate Hyper multi-objective evolutionary algorithm
ISSN:	1432-7643, 1433-7479
Online Access:	Get full text
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