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An Efficient Ant Colony System Based on Receding Horizon Control for the Aircraft Arrival Sequencing and Scheduling Problem

机译:基于后视控制的高效蚁群系统对飞机进场排序与调度的影响

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摘要

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficiency.
机译:飞机到达排序和调度(ASS)问题是空中交通管制(ATC)中的一个突出问题,事实证明这很难确定性多项式(NP)。本文以排列问题的形式表述ASS问题,并提出了一种新的解决方案框架,该框架首次尝试使用基于后视层控制(RHC)的蚁群系统(ACS)算法来解决该问题。由此产生的针对ASS问题的RHC改进的ACS算法(称为RHC-ACS-ASS算法)是鲁棒,有效和高效的,这不仅是因为ACS算法具有强大的全局搜索能力,而且已被证明是合适的对于此类NP难题,也是由于RHC技术可以用后退的时间窗对问题进行划分,从而减轻了计算负担并提高了解决方案的质量。 RHC-ACS-ASS算法已针对文献中的案例和随机生成的案例进行了广泛的测试。还对ACS和RHC参数对算法性能的影响进行了综合研究。此外,通过使用两次选择交换启发式局部搜索进一步增强了所提出的算法。实验结果证明,所提出的RHC-ACS-ASS算法在解决ASS问题时通常不使用RHC技术和遗传算法(GA)优于普通ACS,并且具有较高的鲁棒性,有效性和效率。

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