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Airport taxi planning: Lagrangian decomposition

机译:机场出租车规划:拉格朗日分解

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摘要

The airport taxi planning (TP) module is a decision tool intended to guide airport surface management operations. TP is defined by a flow network optimization model that represents flight ground movements and improves aircraft taxiing routes and schedules during periods of aircraft congestion. TP is not intended to operate as a stand-alone tool for airport operations management: on the contrary, it must be used in conjunction with existing departing and arriving traffic tools and overseen by the taxi planner of the airport, also known as the aircraft ground controller. TP must be flexible in order to accommodate changing inputs while maintaining consistent routes and schedules already delivered from past executions. Within this dynamic environment, the execution time of TP may not exceed a few minutes. Classic methods for solving binary multi-commodity flow networks with side constraints are not efficient enough; therefore, a Lagrangian decomposition methodology has been adapted to solve it. We demonstrate TP Lagrangian decomposition using actual data from the Madrid-Barajas Airport.
机译:机场滑行计划(TP)模块是旨在指导机场地面管理操作的决策工具。 TP由流网络优化模型定义,该模型代表飞行地面运动并在飞机拥堵期间改善飞机滑行路线和时间表。 TP并非旨在作为用于机场运营管理的独立工具:相反,它必须与现有的出发和到达交通工具结合使用,并由机场的出租车计划者(也称为飞机场)进行监督控制器。 TP必须具有灵活性,以便适应不断变化的输入,同时保持从过去执行中已经交付的一致路线和进度表。在这种动态环境中,TP的执行时间可能不会超过几分钟。解决带有边约束的二元多商品流网络的经典方法效率不高。因此,拉格朗日分解方法已被采用来解决它。我们使用马德里-巴拉哈斯机场的实际数据演示了TP拉格朗日分解。

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