Runway systems are among the most stringent bottlenecks at global hub airports, which have been identified as a major source of airport inefficiency. Runway system inefficiencies are manifested in multiple dimensions such as delay, throughput reduction and excessive emission, whose tradeoffs are investigated in this paper as part of an airport runway scheduling problem in the presence of uncertainty. We formulate a multi-objective optimization model aiming to minimize flight delays, maximize airport throughput, and minimize aircraft emissions, subject to a variety of constraints such as minimum separation, time window, runway occupancy and flight turnaround. The computational performance is enhanced with an efficient multi-objective evolutionary algorithm, with two mechanisms of adaptive and controllable time-coding and objective-guided individual selection. The proposed method is flexible in adjusting conservatism when it comes to optimization with uncertainty, and offers a set of Pareto optimal solutions for different stakeholders without using scalarization of different objectives. A real-world case study is carried out for one of the world’s buiest airports, Shanghai Pudong, under the case of 2 runways, 2 operation types, 12 uncertain conditions and 4 tradeoff scenarios. The computational results show that the proposed optimized method has overall advantages in improving the runway scheduling performance over some meta-heuristics and the First Come First Served strategy. The tradeoff analysis reveals that the minimum delay schedule is preferable for balancing delay, throughtput and emission. The findings provide managerial insights regarding traffic management measures for different stakeholders at high-density airports.

跑道系统是全球枢纽机场最严格的瓶颈之一，这些瓶颈已被确认为机场效率低下的主要根源。跑道系统的效率低下表现在多个方面，例如延误，吞吐量减少和排放过多，在存在不确定性的情况下，本文将其权衡作为机场跑道调度问题的一部分进行了研究。我们制定了一个多目标优化模型，旨在最小化航班延误，最大化机场吞吐量和最小化飞机排放，但要遵守各种限制，例如最小间隔，时间窗口，跑道占用和飞行周转。高效的多目标进化算法提高了计算性能，具有自适应和可控时间编码以及目标指导的个人选择的两种机制。所提出的方法在不确定性优化时可以灵活地调整保守性，并且为不同的利益相关者提供了一组Pareto最优解决方案，而无需使用不同目标的标量。我们以2条跑道，2种运营类型，12种不确定条件和4种折衷方案为例，对世界上最舒适的机场之一上海浦东进行了实际案例研究。计算结果表明，与某些元启发式算法和“先到先得”策略相比，所提出的优化方法在提高跑道调度性能方面具有总体优势。权衡分析表明，最小延迟计划对于平衡延迟，吞吐量和排放是更可取的。