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Bio-Inspired Optimization Algorithm Associated with Reinforcement Learning for Multi-Objective Operating Planning in Radioactive Environment

文献类型：期刊论文

作者Kong, Shihan1; Wu, Fang2; Liu, Hao3; Zhang, Wei3; Sun, Jinan4; Wang, Jian5; Yu, Junzhi1
刊名BIOMIMETICS
出版日期2024-07-01
卷号9期号:7页码:17
关键词reinforcement learning improved genetic algorithm radioactive environment planning bio-inspired optimization algorithm combinatorial algorithm
DOI10.3390/biomimetics9070438
通讯作者Yu, Junzhi(yujunzhi@pku.edu.cn)
英文摘要This paper aims to solve the multi-objective operating planning problem in the radioactive environment. First, a more complicated radiation dose model is constructed, considering difficulty levels at each operating point. Based on this model, the multi-objective operating planning problem is converted to a variant traveling salesman problem (VTSP). Second, with respect to this issue, a novel combinatorial algorithm framework, namely hyper-parameter adaptive genetic algorithm (HPAGA), integrating bio-inspired optimization with reinforcement learning, is proposed, which allows for adaptive adjustment of the hyperparameters of GA so as to obtain optimal solutions efficiently. Third, comparative studies demonstrate the superior performance of the proposed HPAGA against classical evolutionary algorithms for various TSP instances. Additionally, a case study in the simulated radioactive environment implies the potential application of HPAGA in the future.
资助项目Beijing Natural Science Foundation[4242038] ; National Natural Science Foundation of China[62203015] ; National Natural Science Foundation of China[62233001] ; National Natural Science Foundation of China[62203436] ; National Natural Science Foundation of China[62273351]
WOS研究方向Engineering ; Materials Science
语种英语
WOS记录号WOS:001276568700001
出版者MDPI
资助机构Beijing Natural Science Foundation ; National Natural Science Foundation of China
源URL[http://ir.ia.ac.cn/handle/173211/59391]  
专题复杂系统管理与控制国家重点实验室_水下机器人
通讯作者Yu, Junzhi
作者单位1.Peking Univ, Coll Engn, Dept Adv Mfg & Robot, State Key Lab Turbulence & Complex Syst, Beijing 100871, Peoples R China
2.SPIC Nucl Energy Co Ltd, Beijing 100029, Peoples R China
3.Beijing Univ Chem Technol, Coll Informat Sci & Technol, Beijing 100029, Peoples R China
4.Peking Univ, Natl Engn Res Ctr Software Engn, Beijing 100871, Peoples R China
5.Chinese Acad Sci, Inst Automat, Lab Cognit & Decis Intelligence Complex Syst, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Kong, Shihan,Wu, Fang,Liu, Hao,et al. Bio-Inspired Optimization Algorithm Associated with Reinforcement Learning for Multi-Objective Operating Planning in Radioactive Environment[J]. BIOMIMETICS,2024,9(7):17.
APA Kong, Shihan.,Wu, Fang.,Liu, Hao.,Zhang, Wei.,Sun, Jinan.,...&Yu, Junzhi.(2024).Bio-Inspired Optimization Algorithm Associated with Reinforcement Learning for Multi-Objective Operating Planning in Radioactive Environment.BIOMIMETICS,9(7),17.
MLA Kong, Shihan,et al."Bio-Inspired Optimization Algorithm Associated with Reinforcement Learning for Multi-Objective Operating Planning in Radioactive Environment".BIOMIMETICS 9.7(2024):17.

入库方式： OAI收割

来源：自动化研究所

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