@inproceedings{771c493a62034c2db3653a043697c785,
title = "A Q-learning-based Automatic Heuristic Design Approach for Seru Scheduling",
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 Programming, Q-learning, Seru Scheduling",
author = "Rongxin Zhan and Zihua Cui and Tao Ma and Dongni Li",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 33rd Chinese Control and Decision Conference, CCDC 2021 ; Conference date: 22-05-2021 Through 24-05-2021",
year = "2021",
doi = "10.1109/CCDC52312.2021.9602499",
language = "English",
series = "Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "253--257",
booktitle = "Proceedings of the 33rd Chinese Control and Decision Conference, CCDC 2021",
address = "United States",
}