Optimisation of Multi-objective Rolling Stock Maintenance Scheduling with Harris’ Hawk Optimiser
2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)(2023)
摘要
In line with Industry 4.0, various advanced technologies such as sensors, automation, and artificial intelligence (AI) methods have been leveraged to enhance maintenance processes in the rolling stock industry. In particular, AI techniques are useful for optimising maintenance scheduling and planning tasks for rolling stocks. This study focuses on the use of a metaheuristic method, namely an enhanced multi-objective Harris’ Hawk optimiser (MO-HHO), for optimising competing objectives based on data obtained from a railway maintenance company. The results of MO-HHO are evaluated and compared with those from other competing models. The findings demonstrate the usefulness of MO-HHO in tackling multi-objective train maintenance scheduling tasks in practical environments.
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关键词
Rolling stock Maintenance,Industry 4.0,Flexible Job Shop,Scheduling,Swarm Intelligence
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