A Multi-Objective Evolutionary Algorithm With Hierarchical Clustering-Based Selection-Reference-Cited by-同舟云学术

A Multi-Objective Evolutionary Algorithm With Hierarchical Clustering-Based Selection

Published:2023 Issue: Volume:11 Page:2557-2569
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Zhou Shenghao¹,Chen Ze²,Li Qi¹,Gu Mengjun³,Bao Zhoucheng¹,He Wenda¹,Sheng Weiguo¹^ORCID

Affiliation:

1. School of Information Science and Technology, Hangzhou Normal University, Hangzhou, China

2. Engineering Research Center of Mobile Health Management System, Hangzhou Normal University, Hangzhou, China

3. China Telecom Corporation Ltd., Zhejiang Branch, Hangzhou, China

Funder

National Natural Science Foundation of China

Scientific Research Fund of Zhejiang Provincial Education Department

Zhejiang Provincial Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10005273.pdf?arnumber=10005273

Reference57 articles.

1. R2-EMOA: Focused Multiobjective Search Using R2-Indicator-Based Selection

2. A Novel Framework for Backstepping-Based Control of Discrete-Time Strict-Feedback Nonlinear Systems With Multiplicative Noises

3. Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion;zhou;Proc IEEE Int Conf Evol Comput,2006

4. Synchronization Control for A Class of Discrete Time-Delay Complex Dynamical Networks: A Dynamic Event-Triggered Approach

5. SMS-EMOA: Multiobjective selection based on dominated hypervolume

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