A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization-Reference-Cited by-同舟云学术

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A Two-Layer Encoding Learning Swarm Optimizer Based on Frequent Itemsets for Sparse Large-Scale Multi-Objective Optimization

Published:2024-06 Issue:6 Volume:11 Page:1342-1357
ISSN:2329-9266
Container-title:IEEE/CAA Journal of Automatica Sinica
language:
Short-container-title:IEEE/CAA J. Autom. Sinica

Author:

Qi Sheng¹^ORCID,Wang Rui¹^ORCID,Zhang Tao¹^ORCID,Yang Xu²^ORCID,Sun Ruiqing²^ORCID,Wang Ling³^ORCID

Affiliation:

1. College of Systems Engineering, National University of Defense Technology,Changsha,China,410073

2. College of Computer, National University of Defense Technology,Changsha,China,410073

3. Tsinghua University,Department of Automation,Beijing,China,100084

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6570654/10539265/10539359.pdf?arnumber=10539359

Reference61 articles.

1. Evolutionary Multitasking with Global and Local Auxiliary Tasks for Constrained Multi-Objective Optimization

2. Multi-Objective Optimization for an Industrial Grinding and Classification Process Based on PBM and RSM

3. Coevolutionary Framework for Generalized Multimodal Multi-Objective Optimization

4. Hybridization of evolutionary algorithm and deep reinforcement learning for multi-objective orienteering optimization

5. A level-based multi-strategy learning swarm optimizer for large-Scale multi-objective optimization

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