A New Hypervolume-Based Evolutionary Algorithm for Many-Objective Optimization

In this article, a new hypervolume-based evolutionary multiobjective optimization algorithm (EMOA), namely, R2HCA-EMOA (R2-based hypervolume contribution approximation EMOA), is proposed for many-objective optimization. The core idea of the algorithm is to use an R2 indicator variant to approximate...

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Bibliographic Details

Published in:	IEEE transactions on evolutionary computation Vol. 24; no. 5; pp. 839 - 852
Main Authors:	Shang, Ke, Ishibuchi, Hisao
Format:	Journal Article
Language:	English
Published:	New York IEEE 01.10.2020 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Approximation algorithms Convergence Evolutionary algorithms hypervolume contribution approximation many-objective optimization Mathematical analysis Monte Carlo methods Multiple objective analysis Optimization Sociology Tensors
ISSN:	1089-778X, 1941-0026
Online Access:	Get full text
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