Offline and Online Objective Reduction via Gaussian Mixture Model Clustering-Reference-Cited by-同舟云学术

Offline and Online Objective Reduction via Gaussian Mixture Model Clustering

Published:2023-04 Issue:2 Volume:27 Page:341-354
ISSN:1089-778X
Container-title:IEEE Transactions on Evolutionary Computation
language:
Short-container-title:IEEE Trans. Evol. Computat.

Author:

Li Genghui¹^ORCID,Wang Zhenkun²^ORCID,Zhang Qingfu³,Sun Jianyong⁴^ORCID

Affiliation:

1. School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen, China

2. School of System Design and Intelligent Manufacturing and the Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China

3. Department of Computer Science, City University of Hong Kong, Hong Kong

4. School of Mathematics and Statistics, Xi’an Jiaotong University, Xi’an, China

Funder

National Natural Science Foundation of China

Hong Kong General Research Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Theoretical Computer Science,Software

Link

http://xplorestaging.ieee.org/ielx7/4235/10089199/09760706.pdf?arnumber=9760706

Reference60 articles.

1. A Pareto Corner Search Evolutionary Algorithm and Dimensionality Reduction in Many-Objective Optimization Problems

2. Multiobjective evolutionary algorithms: a comparative case study and the strength Pareto approach

3. Objective Reduction in Evolutionary Multiobjective Optimization: Theory and Applications

4. PlatEMO: A MATLAB Platform for Evolutionary Multi-Objective Optimization [Educational Forum]

5. An objective reduction algorithm using representative Pareto solution search for many-objective optimization problems

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