DQN-based aircraft overhaul workshop real-time scheduling method

Abstract

The invention discloses a DQN-based aircraft overhaul real-time scheduling method, and belongs to the field of machine learning and intelligent manufacturing. Real-time information of an airplane overhaul workshop is obtained through the Internet of Things technology, and on the basis, a Markov decision model about the airplane overhaul workshop scheduling problem is established. The DQN method istrained by using the real-time information, so that the DQN method has a self-adaptive aircraft overhaul workshop real-time scheduling capability. And meanwhile, two Q networks with the same structure and an experience playback strategy are used for improving the training speed and the training effect of the DQN method. When the method is used for real-time scheduling of the aircraft overhaul workshop, the aircraft overhaul completion time can be effectively shortened.

Description

technical field

[0001] The invention belongs to the field of machine learning and intelligent manufacturing, and in particular relates to a DQN-based real-time scheduling method for an aircraft overhaul workshop. Background technique

[0002] In order to improve market competitiveness, aircraft overhaul enterprises must formulate reasonable scheduling strategies. Traditional aircraft overhaul workshop scheduling methods mainly focus on the application of traditional intelligent algorithms. However, as today's aircraft overhaul process becomes more and more complex, the environment of the overhaul workshop has become unpredictable, and the traditional scheduling method can no longer meet the needs of the overhaul process; the traditional scheduling method assigns tasks in advance without considering the real-time information of the workshop , leading to a large deviation between the plan and the actual production, such as the literature "Zhuang Xincun, Lu Yuhao, Li Congxin. W...

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