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A Novel Self-Adjusting Dual-Mode Evolutionary Framework for Multi-Task Optimization

Yingbo Xie Junfei Qiao Ding Wang Manman Yuan

自动化学报（英文版）2025，Vol.12Issue(11)：2239-2252,14.

自动化学报（英文版）2025，Vol.12Issue(11)：2239-2252,14.DOI:10.1109/JAS.2025.125273

A Novel Self-Adjusting Dual-Mode Evolutionary Framework for Multi-Task Optimization

Yingbo Xie ¹Junfei Qiao ²Ding Wang ²Manman Yuan¹

作者信息

1. School of Electrical Engineering and Automation,Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment,Henan Polytechnic University,Jiaozuo 454003,China
2. School of Information Sciences and Technology,the Beijing Key Laboratory of Computational Intelligence and Intelligent System,and the Beijing Laboratory of Smart Environmental Protection,Beijing University of Technology,Beijing 100124,China
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摘要

关键词

Evolutionary algorithms/evolutionary multitasking/knowledge transfer/optimization problem

Key words

Evolutionary algorithms/evolutionary multitasking/knowledge transfer/optimization problem

引用本文复制引用

Yingbo Xie,Junfei Qiao,Ding Wang,Manman Yuan..A Novel Self-Adjusting Dual-Mode Evolutionary Framework for Multi-Task Optimization[J].自动化学报（英文版）,2025,12(11):2239-2252,14.

基金项目

This work was supported in part by the Plan of Key Scientific Research Projects of Colleges and Universities in Henan Province(25A413005,24A120005),the National Science and Technology Major Project(2021ZD0112302),and the National Natural Science Foundation of China(62222301,61890930-5,62021003). （25A413005,24A120005）

自动化学报（英文版）

ISSN：2329-9266

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