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Dual-self-learning co-evolutionary algorithm for energy-efficient flexible job shop scheduling problem with processing- transportation composite robots.

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第一作者： Meizhou,Zhang

第一单位： Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, 430081, China.;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China.

作者： Meizhou,Zhang ^[1] ; Min,Zhou ^[1] ; Liping,Zhang ^[2] ; Zikai,Zhang ^[3]

作者单位： Key Laboratory of Metallurgical Equipment and Control Technology, Ministry of Education, Wuhan University of Science and Technology, Wuhan, 430081, China.;Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China. ^[1] Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China. zhangliping@wust.edu.cn.;Precision Manufacturing Institute, Wuhan University of Science and Technology, Wuhan, 430081, China. zhangliping@wust.edu.cn. ^[2] Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering, Wuhan University of Science and Technology, Wuhan, 430081, China.;Precision Manufacturing Institute, Wuhan University of Science and Technology, Wuhan, 430081, China. ^[3]

关键词 Co-evolutionary algorithm Energy-efficient flexible job shop scheduling Multi-objective optimization Processing-transportation composite robots Self-learning

DOI 10.1038/s41598-025-11890-2

PMID 40913072

发布时间 2025-09-08

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