A Q-learning-based Automatic Heuristic Design Approach for Seru Scheduling

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@InProceedings{Zhan:2021:CCDC,

• author = "Rongxin Zhan and Zihua Cui and Tao Ma and Dongni Li",
• title = "A Q-learning-based Automatic Heuristic Design Approach for Seru Scheduling",
• booktitle = "2021 33rd Chinese Control and Decision Conference (CCDC)",
• year = "2021",
• pages = "253--257",
• abstract = "Seru production is a new mode of production with the advantages of quick response, high flexibility and high efficiency. It is well suited to the market that fluctuates frequently. The seru scheduling is an important issue for seru production system configuration problem because it reflects the management and control principle of seru production systems, which called just-in-time operation system. This paper studies a seru scheduling problem, which can be described as how to determine the sequence of serus in limited space for multiple orders considering worker overlapping. The objective is to minimize the maximum completion time. A Q-learning-based genetic programming algorithm is proposed to solve the above problem. Experimental results show the effectiveness of the proposed algorithm.",
• keywords = "genetic algorithms, genetic programming, Production systems, Processor scheduling, Evolutionary computation, Aerospace electronics, Scheduling, Computational efficiency, Seru Scheduling, Q-learning",
• DOI = "doi:10.1109/CCDC52312.2021.9602499",
• ISSN = "1948-9447",
• month = may,
• notes = "Also known as \cite{9602499}",

}

Genetic Programming entries for Rongxin Zhan Zihua Cui Tao Ma Dongni Li

Citations