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Optimization of noise abatement aircraft terminal routes using a multi-objective evolutionary algorithm based on decomposition

机译:基于分解的多目标进化算法优化消音飞机的航路

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Recently, a multi-objective evolutionary algorithm based on decomposition (MOEA/D) has emerged as a potential method for solving multi-objective optimization problems (MOPs) and attracted much attention from researchers. In MOEA/D, the MOPs are decomposed into a number of scalar optimization sub-problems, and these sub-problems are optimized concurrently by only utilizing the information from their neighboring sub-problems. Thanks to these advantages, MOEA/D has demonstrated to be more efficient than the non-dominated sorting genetic algorithm II (NSGA-II) and other methods. However, its applications to practical problems are still limited, especially in the domain of aerospace engineering. Therefore, this paper aims to present a new application of MOEA/D for the optimal design of noise abatement aircraft terminal routes. First, in order to optimize aircraft noise for aircraft terminal routes while taking into account the interests of various stakeholders, bi-objective optimization problems including noise and fuel consumption are formulated, in which both the ground track and vertical profile of a terminal route are optimized simultaneously. Then, MOEA/D is applied to solve these problems. Furthermore, to ensure the design space of vertical profiles is always feasible during the optimization process, a trajectory parameterization technique recently proposed is also used. This technique aims at reducing the number of model evaluations of MOEA/D and hence the computational cost will decrease significantly. The efficiency and reliability of the developed method are evaluated through case studies for departure and arrival routes at Rotterdam The Hague Airport in the Netherlands.
机译:近年来,基于分解的多目标进化算法(MOEA / D)成为解决多目标优化问题(MOP)的一种潜在方法,引起了研究者的广泛关注。在MOEA / D中,MOP被分解为多个标量优化子问题,并且仅通过利用来自其相邻子问题的信息来同时优化这些子问题。由于这些优点,MOEA / D已被证明比非主导的排序遗传算法II(NSGA-II)和其他方法更有效。但是,它在实际问题中的应用仍然受到限制,特别是在航空航天工程领域。因此,本文旨在提出MOEA / D在降噪飞机航站楼路线优化设计中的新应用。首先,为了在考虑各种利益相关者利益的同时优化飞机航站楼路线的飞机噪声,提出了包括噪声和燃油消耗在内的双目标优化问题,其中对航道的地面轨迹和垂直剖面进行了优化同时。然后,采用MOEA / D解决这些问题。此外,为了确保在优化过程中垂直轮廓的设计空间始终是可行的,最近还提出了一种轨迹参数化技术。该技术旨在减少MOEA / D的模型评估次数,因此计算成本将大大降低。通过对荷兰鹿特丹海牙机场出发和到达航线的案例研究,评估了所开发方法的效率和可靠性。

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