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作 者:王兴隆[1] 丁俊峰 WANG Xing-long;DING Jun-feng(Key Laboratory of Internet of Aircrafts,Civil Aviation University of China,Tianjin 300300,China;College of Computer Science and Technology,Civil Aviation University of China,Tianjin 300300,China)
机构地区:[1]中国民航大学民航飞联网重点实验室,天津300300 [2]中国民航大学计算机科学与技术学院,天津300300
出 处:《科学技术与工程》2023年第10期4440-4447,共8页Science Technology and Engineering
基 金:国家重点研发计划(2020YEB1600101);天津市自然科学重点项目(2020ZD01)。
摘 要:针对现行“先到先服务”的机场除冰车调度方式效率不高的问题。以最小化除冰车行驶总距离和航空器等待总时间为目标函数,构建机位除冰车辆和航空器协同调度模型,并提出一种改进的遗传算法对模型进行求解。采用西安机场某天142条航班数据进行仿真实验,并与随机调度算法和贪心算法进行比较。结果表明,改进的遗传算法相较于随机调度算法和贪心算法分别节约15.23%和7.81%的行驶总距离,且航空器等待除冰时间大幅度减少。证明了所提算法在指导除冰车作业方面的优越性。The current“first come,first serve”airport deicing vehicle scheduling method is inefficient.Taking minimizing the total distance of the deicing vehicle and the total waiting time of the aircraft as the objective function,the cooperative scheduling model of the stand deicing vehicle and the aircraft was constructed,and an improved genetic algorithm was proposed to solve the model.The simulation experiment was carried out with 142 flight data of Xi'an Airport,and compared with random scheduling algorithm and greedy algorithm.The results show that compared with random scheduling algorithm and greedy algorithm,the improved genetic algorithm saves 15.23%and 7.81%of the total travel distance respectively,and the aircraft waiting time for deicing is greatly reduced.The superiority of the proposed algorithm in guiding the operation of deicing truck is proved.
分 类 号:V351.392[航空宇航科学与技术—人机与环境工程]
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