A multi-objective nonlinear integer programming model for mixed runway operations within the TMAs

Z. Kaplan, C. Çetek, T. Saraç
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引用次数: 0

Abstract

Global air traffic demand has shown rapid growth for the last three decades. This growth led to more delays and congestion within terminal manoeuvring areas (TMAs) around major airports. The efficient use of airport capacities through the careful planning of air traffic flows is imperative to overcome these problems. In this study, a mixed-integer nonlinear programming (MINLP) model with a multi-objective approach was developed to solve the aircraft sequencing and scheduling problem for mixed runway operations within the TMAs. The model contains fuel cost functions based on airspeed, altitude, bank angle, and the aerodynamic characteristics of the aircraft. The optimisation problem was solved by using the $\varepsilon$ -constraint method where total delay and total fuel functions were simultaneously optimised. We tested the model with different scenarios generated based on the real traffic data of Istanbul Sabiha Gökçen Airport. The results revealed that the average total delay and average total fuel were reduced by 26.4% and 6.7%, respectively.
TMAs内混合跑道运行的多目标非线性整数规划模型
过去三十年来,全球空中交通需求呈现出快速增长的趋势。这一增长导致主要机场周围的终端操纵区(tma)出现更多延误和拥堵。为了克服这些问题,必须通过仔细规划空中交通流量来有效利用机场能力。本文建立了一种多目标混合整数非线性规划(MINLP)模型,用于求解TMAs内混合跑道运行的飞机排序和调度问题。该模型包含基于空速、高度、倾斜角和飞机气动特性的燃料成本函数。采用同时优化总延迟函数和总燃料函数的$\varepsilon$约束方法求解优化问题。我们使用基于伊斯坦布尔Sabiha Gökçen机场真实交通数据生成的不同场景对模型进行了测试。结果表明,平均总延误和平均总燃油分别减少了26.4%和6.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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