基于速度分配的航空器绿色滑行优化

针对航班量过快增长以及机场容量限制导致的机场滑行道拥堵问题，在航空器滑行路径优化的基础上，提出一种基于遗传算法和Yen算法的速度优化方法。首先规定速度变化剖面，以滑行时间和尾气排放为目标，以最大滑行速度和加速度为决策变量，考虑机场滑行规则和滑行限制设定约束条件，建立滑行路径和速度的优化模型；然后利用Yen算法对浦东机场16架航空器的滑行路径进行预筛选，为每个航空器分配3条路径；最后利用遗传算法进行仿真求解，依据最小滑行成本得到最优的滑行路径和速度分配方案。结果表明，优化后的滑行时间降低21.82%，尾气排放降低27.17%，滑行成本降低25.77%，且未产生冲突。可见本文建立的优化模型和方法对提高场面运行效率和减少航空污染具有一定的可行性。

Optimization of Aircraft Green Taxi Based on Speed Allocation

In order to solve the problem of congestion on airport taxiway caused by the excessive growth of flight number and the limitation of airport capacity, based on the optimization of aircraft taxi path, a speed optimization approach based on genetic algorithm and Yen algorithm was proposed. Firstly, the speed change profile was specified and an optimization model for taxi path and speed was established which took minimum taxiing time and exhaust emission as objectives and took maximum taxiing speed and acceleration as decision variables. And the constraints were set considering the airport taxi rules and taxi restrictions. Then, the Yen algorithm was used to pre-screen the taxi paths of 16 aircraft at Pudong Airport, and 3 paths of each aircraft were generated. Finally, the genetic algorithm is used to simulate, and the optimal taxi path and speed allocation strategy is obtained according to the minimum taxi cost. The results show that the optimized taxiing time is reduced by 21.82%, the exhaust emissions is reduced by 27.17%, the taxiing cost is reduced by 25.77%, and there is no conflict. It is concluded that the optimization model and method established have certain feasibility to improve surface operation efficiency and reduce aviation pollution.