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基于遗传算法的飞机垃圾车计划恢复模型OA北大核心CSTPCD

Aircraft garbage truck planning recovery model based on the genetic algorithm

中文摘要英文摘要

利用人工经验调度地面保障车辆,难以在突发状况发生时确保地面车辆的合理调度,从而导致航班的集体延误和地面保障车辆资源的浪费.针对机场垃圾车调度的上述问题,在硬时间窗限制及多种约束条件下,以飞机垃圾车调度总成本最小为目标函数构建计划恢复模型.算例分析结果表明:相对于人工恢复调度费,该文计划恢复模型调度费节约了 46.44%.因此,该文计划恢复模型具有可行性.

The use of manual experience in the dispatch of ground support vehicles makes it difficult to ensure the proper dispatch of ground vehicles in the event of unforeseen circumstances,which leads to collective delays in flights and wastage of ground support vehicle resources.A planning recovery model was constructed aiming at the aforementioned problems of airport garbage truck scheduling,with the objective function of minimizing the total cost of aircraft garbage truck scheduling under hard time window limitations and multiple constraints.The analysis result of the example showed that compared with the manual recovery scheduling cost,a 46.44%saving in scheduling cost was achieved by the planning recovery model proposed in this paper.Therefore,the feasibility of the planning recovery model was demonstrated.

史浩祥;易奎;牟奇锋

中国民用航空飞行学院 机场学院,四川 广汉 618307中国民用航空局 第二研究所,四川 成都 610041

计算机与自动化

车辆调度时间窗计划恢复遗传算法成本最优

vehicle schedulingtime windowplanning recoverygenetic algorithmcost optimization

《安徽大学学报(自然科学版)》 2024 (003)

68-74 / 7

国家重点研发计划项目(2021YFB1600500);四川省科技计划项目(2022JDRC0077)

10.3969/j.issn.1000-2162.2024.03.010

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