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Knowledge-transfer based genetic programming algorithm for multi-objective dynamic agile earth observation satellite scheduling problem

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成果类型:
期刊论文
作者:
Wei, Luona;Chen, Ming;Xing, Lining;Wand, Qian;Song, Yanjie;...
通讯作者:
Chen, YN
作者机构:
[Wei, Luona] South Cent Minzu Univ, Coll Elect & Informat Engn, Wuhan 430074, Peoples R China.
[Chen, YN; Chen, Ming; Chen, Yuning; Chen, Yingwu] Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Peoples R China.
[Xing, Lining] Xidian Univ, Coll Elect Engn, Xian 710126, Peoples R China.
[Wand, Qian] Cent China Normal Univ, Natl Engn Res Ctr Educ Big Data, Wuhan 430079, Peoples R China.
[Song, Yanjie] Natl Def Univ, Beijing 100091, Peoples R China.
通讯机构:
[Chen, YN ] N
Natl Univ Def Technol, Coll Syst Engn, Changsha 410073, Peoples R China.
语种:
英文
关键词:
Agile satellite scheduling;Multi-objective;Genetic programming;Knowledge transfer
期刊:
Swarm and Evolutionary Computation
ISSN:
2210-6502
年:
2024
卷:
85
页码:
101460
基金类别:
National Natural Science Foundation of China [62307015, 71701203, 72001212]; Hubei Provincial Natural Science Foundation of China [2023AFB295]; Knowledge Innovation Program of Wuhan-Shugung Project, China [2023010201020390]; Hu-nan Postgraduate Research Innovation Project, China [CX20210034]; China Postdoctoral Science Foundation [2023M741304]
机构署名:
本校为其他机构
摘要:
The multi -objective dynamic agile earth observation satellite scheduling problem (MO-DAEOSSP) aims to schedule a set of real-time arrival requests and form a reasonable observation plan to satisfy various criteria. According to the requirements in practical applications, the total profit and the average image quality of scheduled requests are taken as optimization goals in this study. Compared to manually designed heuristics and iterative -based methods used in previous research, genetic programming based hyper heuristics (GPHH) can automatically evolve high -quality heuristic rules (HRs) for...

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