Delay, Throughput and Emission Tradeoffs in Airport Runway Scheduling with Uncertainty Considerations
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Delay, Throughput and Emission Tradeoffs in Airport Runway Scheduling with Uncertainty Considerations Jianan Yin 1,2 Hua Xie 1
& Yuanyuan
Ma 3
& Yuxin
Hu 3 & Ke Han 4
& Suwan
Yin 2 &
Accepted: 1 September 2020/ # Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract 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 multiobjective 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. Keywords Air traffic management . Runway scheduling . Performance tradeoff .
Uncertainty . Multi-objective optimization . Evolutionary algorithm
* Jianan Yin [email protected] Extended author information available on the last page of the article
Yin J. et al.
Nomenclature ARSP Airport Runway Scheduling Problem ATM Air Traffic Management EMOE Efficient Multi-Objective Evolutionary ACTC Adaptive and Controllable Time-Coding OGIS Objective-Guided Individual Selection TMA Terminal Manoeuvring Area FCFS First Come First Served
1 Introduction Airports are the key nodes of an air transport network. Their operational efficiency is, therefore, crucial to the system-wide performance of national airspace system. It has been reported that the bottleneck of air traffic operations has been shifted from en-route airspace to the airports (Smeltink et al. 2003; Yin et al. 2019), partly due to the consistent improvements made in the en-route air traffic management. At many hub airports, the insufficient capacity can
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