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检索条件"主题词=Multifactorial Evolutionary Algorithm"
42 条 记 录,以下是21-30 订阅
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An efficient strategy for using multifactorial optimization to solve the clustered shortest path tree problem
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APPLIED INTELLIGENCE 2020年 第4期50卷 1233-1258页
作者: Thanh, Pham Dinh Binh, Huynh Thi Thanh Trung, Tran Ba Taybac Univ Fac Math Phys Informat Son La Vietnam Hanoi Univ Sci & Technol Sch Informat & Commun Technol Hanoi Vietnam
Arising from the need of all time for optimization of irrigation systems, distribution network and cable network, Clustered Shortest-Path Tree Problem (CluSPT) has been attracting a lot of attention and interest from ... 详细信息
来源: 评论
Multi-objective evolutionary multi-tasking algorithm using cross-dimensional and prediction-based knowledge transfer
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INFORMATION SCIENCES 2022年 586卷 540-562页
作者: Chen, Qunjian Ma, Xiaoliang Yu, Yanan Sun, Yiwen Zhu, Zexuan Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen Peoples R China BGI Shenzhen Shenzhen 518083 Peoples R China Shenzhen Univ Sch Biomed Engn Shenzhen Peoples R China
Transfer learning is an important research topic in machine learning and recently has been introduced into evolutionary computation to form evolutionary multi-task optimization (EMTO). EMTO focuses on tackling multipl... 详细信息
来源: 评论
System-in-package design using multi-task memetic learning and optimization
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MEMETIC COMPUTING 2022年 第1期14卷 45-59页
作者: Dai, Weijing Wang, Zhenkun Xue, Ke Southern Univ Sci & Technol Sch Syst Design & Intelligent Mfg Shenzhen Peoples R China Southern Univ Sci & Technol Dept Comp Sci & Engn Shenzhen Peoples R China
System-in-Package (SiP) is an advanced packaging technology and developing rapidly in semiconductor industry. Electronic modules of this package type are individual integrated systems for specific applications. Theref... 详细信息
来源: 评论
Towards urban energy sustainability and resiliency through smart and effective renewable resource allocation
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SUSTAINABLE CITIES AND SOCIETY 2024年 107卷
作者: Cheng, Lijun Samah, Azurah Zhang, Yubo Jia, Zongwei Li, Fuzhong Univ Technol Malaysia Fac Comp Skudai Malaysia Shanxi Agr Univ Sch Software Taigu 030801 Shanxi Peoples R China Shanxi Agr Univ Sch Informat Sci & Engn Taigu 030801 Shanxi Peoples R China
Urban energy sustainability and resiliency are paramount in addressing the challenges of modern urbanization. This paper introduces a novel framework that seamlessly integrates smart agriculture practices with an effe... 详细信息
来源: 评论
Multitask Augmented Random Search in deep reinforcement learning
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APPLIED SOFT COMPUTING 2024年 160卷
作者: Thanh, Le Tien Thang, Ta Bao Van Cuong, Le Binh, Huynh Thi Thanh Grad Univ Adv Studies Dept Informat SOKENDAI Tokyo Japan Hanoi Univ Sci & Technol Sch Informat & Commun Technol Hanoi Vietnam
Reinforcement Learning (RL) has gained significant popularity in recent years for its ability to solve complex control problems. However, most existing RL algorithms are designed to train policies for each environment... 详细信息
来源: 评论
evolutionary Multitask Optimization: a Methodological Overview, Challenges, and Future Research Directions
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COGNITIVE COMPUTATION 2022年 第3期14卷 927-954页
作者: Osaba, Eneko Del Ser, Javier Martinez, Aritz D. Hussain, Amir Basque Res & Technol Alliance BRTA TECNALIA Ed 700 Derio 48160 Spain Univ Basque Country UPV EHU Bilbao 48013 Spain Edinburgh Napier Univ Edinburgh Midlothian Scotland
In this work, we consider multitasking in the context of solving multiple optimization problems simultaneously by conducting a single search process. The principal goal when dealing with this scenario is to dynamicall... 详细信息
来源: 评论
Contrastive variational auto-encoder driven convergence guidance in evolutionary multitasking
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APPLIED SOFT COMPUTING 2024年 163卷
作者: Wang, Ruilin Feng, Xiang Yu, Huiqun Shanghai Engn Res Ctr Smart Energy Shanghai 200237 Peoples R China
Knowledge transfer is at the core of the evolutionary Multitasking (EMT) problem, as it exploits the interaction of inter-task common knowledge to accelerate task convergence. However, existing research on EMT is gene... 详细信息
来源: 评论
Two levels approach based on multifactorial optimization to solve the clustered shortest path tree problem
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evolutionary INTELLIGENCE 2022年 第1期15卷 185-213页
作者: Huynh Thi Thanh, Binh Pham Dinh, Thanh Hanoi Univ Sci & Technol Sch Informat & Commun Technol Hanoi Vietnam Taybac Univ Fac Nat Sci & Technol Son La Vietnam
The Clustered Shortest-Path Tree Problem (CluSPT) has a great meaning in theoretical research as well as a wide range of applications in everyday life, especially in the field of network optimization. Being able to so... 详细信息
来源: 评论
evolutionary Constrained Multi-task Optimization: Benchmark Problems and Preliminary Results  22
Evolutionary Constrained Multi-task Optimization: Benchmark ...
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Genetic and evolutionary Computation Conference (GECCO)
作者: Li, Yanchi Gong, Wenyin Li, Shuijia Univ Geosci Sch Comp Sci China Wuhan Peoples R China
Multi-task optimization (MTO) aims to solve multiple tasks simultaneously. However, multi-task evolutionary algorithms (MTEAs) hardly consider the problem with constraints, while most optimization problems, in reality... 详细信息
来源: 评论
multifactorial Differential Evolution with Opposition-based Learning for Multi-tasking Optimization
Multifactorial Differential Evolution with Opposition-based ...
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IEEE Congress on evolutionary Computation (IEEE CEC)
作者: Yu, Yanan Zhu, Anmin Zhu, Zexuan Lin, Qiuzhen Yin, Jian Ma, Xiaoliang Shenzhen Univ Coll Comp Sci & Software Engn Shenzhen 518060 Guangdong Peoples R China
Recently, multi-tasking optimization (MTO) has become a rising research topic in the field of evolutionary computation that has attracted increasing attention of academia. Comparing with single-objective optimization ... 详细信息
来源: 评论