Energy Consumption Oriented Dynamic Flexible Job Shop Online Scheduling with GPHH

Created by W.Langdon from gp-bibliography.bib Revision:1.8355

@InProceedings{Xu:2023:RICAI,

• author = "Binzi Xu and Chun Wang and Dengchao Huang and Xiongfeng Deng",
• title = "Energy Consumption Oriented Dynamic Flexible Job Shop Online Scheduling with {GPHH}",
• booktitle = "2023 5th International Conference on Robotics, Intelligent Control and Artificial Intelligence (RICAI)",
• year = "2023",
• pages = "508--512",
• month = dec,
• keywords = "genetic algorithms, genetic programming, Energy consumption, Green manufacturing, Job shop scheduling, Dynamic scheduling, Market research, Dispatching, smart manufacturing, GPHH, dispatching rules, terminals",
• DOI = "doi:10.1109/RICAI60863.2023.10489448",
• abstract = "With the overwhelming trend of smart manufacturing and green manufacturing, an automatic scheduling method is urgently required for dynamic flexible job shop (DFJSS) to optimise energy consumption and meet the green indicator. To address this, this paper focuses on using genetic programming hyper-heuristic (GPHH) to generate dispatching rules (DRs) which can make scheduling decision online to minimise the energy consumption. First, the energy flow in DFJSS is analysed and two objectives (i.e., mean tardiness and ratio of useless energy consumption) are established, then energy consumption related terminals are designed to offer corresponding information to DRs. DRs generated by GPHH are compared with manually designed DRs, and the results shows the goodness of generated DRs. Besides, the parameters of GPHH are also analysed for a better performance and deeper understanding.",
• notes = "Also known as \cite{10489448}",

}

Genetic Programming entries for Binzi Xu Chun Wang Dengchao Huang Xiongfeng Deng

Citations