A real-time integrated optimization of the aircraft holding time and rerouting under risk area
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A real-time integrated optimization of the aircraft holding time and rerouting under risk area Linlin Chen1 · Shuihua Han1 · Chaokan Du1 · Zongwei Luo2 Accepted: 25 September 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Fight on-time rate is one of the key air transport industry’s service quality indicators, often affected by adverse weather. In order to improve flight punctuality and reduce the impact of adverse weather on flights, a Real-time Integrated Optimization of the Aircraft Holding Time and Rerouting under Risk Area (RIOAHTR-RA) model is proposed at minimizing the total flight duration from the start point of rerouting to the end point of rerouting under adverse weather condition. In this model, the update cycle based on radar data is generally 6 min, and the position relationship between risk area and the aircraft is available and described in real time. The RIOAHTR-RA model is then solved by the distribution estimation algorithm with improved artificial potential field (IAPF) by introducing intermediate target point, relative position and relative velocity factors. Then, the optimal holding time and rerouting path for aircraft were allocated. The results are compared with the single rerouting strategy, and the effectiveness of the optimization solver with improved IAPF is evaluated. Compared with the data of the Hong Kong Observatory’s forecast system, the results show that appropriate holding time before rerouting can reduce flight delays. The proposed RIOAHTR-RA model is suitable for real-time air traffic flow management. Keywords Air traffic flow management · Holding time · Rerouting · Integrated optimization · Adverse weather · Real-time
Linlin Chen and Shuihua Han have contributed equally to this work.
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Zongwei Luo [email protected] Linlin Chen [email protected] Shuihua Han [email protected] Chaokan Du [email protected]
1
Department of Management Science, School of Management, Xiamen University, Xiamen 361005, China
2
BNU-UIC Institute of AI and Future Networks, Beijing Normal University-Zhuhai, BNU-HKBU United International College, Zhuhai, China
123
Annals of Operations Research
1 Introduction With the rapid development of air transport industry, a large number of flight delays have been observed. According to the Airline On-time Performance Report (Flight states 2019), the average on-time arrival rate of 41 major international airlines in July 2019 was 75.39%, and the average delay time was 59.8 min, causing various economic problems. As an important external factor affecting flight delay, adverse weather is still one of the obstacles in improving flight punctuality (Coy 2006; Koetse and Rietveld 2009; Federal Aviation Administration 2020). The adverse weather objectives are further extended to the safe range, namely risk area (Thomas et al. 2016). Faced with risk area, there are generally two solutions. First is the ground or air holding strategy, a traditional solution for many airlines is, to have flights wait on the ground or in the air
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