The invention discloses a flight landing scheduling method based on an improved DQN (deep Q network) algorithm, and belongs to the technical field of flight scheduling. According to the method, the problems that in a traditional flight landing scheduling algorithm, the aircraft landing cost is too high, and the traditional DQN action space is limited are solved. The method comprises the followingsteps of 1, constructing a landing cost model suitable for deep reinforcement learning according to to-be-landed aircraft information; 2, establishing a deep reinforcement learning agent; 3, calculating a specific landing time sequence and the minimum cost of landing in the sequence by using an improved algorithm; and 4, transmitting the aircraft landing sequence and the corresponding minimum costto the landing cost model, calculating a return and returning the return to the intelligent agent. The sequence of a group of aircrafts is output by utilizing the DQN, and the specific landing time and the total landing cost of each aircraft in the group of aircrafts are calculated through the improved algorithm.
本发明公开一种基于改进DQN(深度Q网络)算法和的航班着陆调度方法,属于航班调度技术领域。本发明解决了传统航班着陆调度算法中飞机着陆成本过大的问题以及传统DQN动作空间有限的问题。包括以下步骤:步骤一,根据待着陆的飞机信息构建适用于深度强化学习学习的着陆成本模型;步骤二,建立深度强化学习智能体;步骤三,用改进的算法计算出以该顺序进行着陆的具体着陆时间序列和最小成本;步骤四,将飞机着陆顺序和对应的最小成本传递给着陆成本模型并计算一个回报返回给智能体。利用DQN网络输出一组飞机的顺序,再通过改进算法计算出一组飞机中每架飞机的具体着陆时间和总着陆成本。
Flight landing scheduling method based on improved DQN algorithm
一种基于改进DQN算法的航班着陆调度方法
2020-04-21
Patent
Elektronische Ressource
Chinesisch
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