摘要
文中将最少使用车辆数目、最短总行驶距离,以及最少时间惩罚成本作为目标,根据实际机场运行情况面向机场地面特种设备车辆构建带有容量限制和时间窗的全种类七车型车辆联合调度约束模型并设计遗传算法求解,通过西安咸阳机场实际航班信息数据进行验证.结果表明:与先到先服务算法相比,设计算法在机场地面保障车辆调度中明显减少车辆的使用数目和行驶距离,相比先到先服务方法减少超过53%的车辆行驶距离和8辆保障车辆,最终降低12.8%的总成本并且有效减少延误.
Taking the minimum number of vehicles used, the shortest total driving distance and the minimum time penalty cost as the objectives, according to the actual airport operation situation, a joint scheduling constraint model of all kinds of seven vehicles with capacity restrictions and time windows was constructed for airport ground special equipment vehicles, and a genetic algorithm was designed to solve it. It is verified by the actual flight information data of Xi’an Xianyang Airport. The results show that compared with the first-come-first-served algorithm, the designed algorithm significantly reduces the number of vehicles used and the driving distance in the airport ground support vehicle scheduling. Compared with the first-come-first-served service method, it reduces the driving distance of vehicles by more than 53% and eight guaranteed vehicles, and finally reduces the total cost by 12.8%.
作者
冯明端
肖雪
周航
FENG Mingduan;XIAO Xue;ZHOU Hang(College of Civil Aviation,Nanjing University of Aeronautics and Astronautics,Nanjing 210000,China)
出处
《武汉理工大学学报（交通科学与工程版）》
2023年第1期67-72,共6页
Journal of Wuhan University of Technology（Transportation Science & Engineering）
基金
国家重点研发计划项目(2018YFC0809500)
国家自然科学基金(71573122,71873081)
江苏省青蓝工程项目(2020)。
关键词
航空运输
多车型车辆联合调度
遗传算法
机场地面保障车辆
多目标优化
air transportation
multi-type vehicle joint scheduling
genetic algorithm
airport ground support vehicles
multi-objective optimization
