主讲人：Andrea D’Ariano

邀请人：王鹏玲 副教授

时间：2025年4月21日（周一）上午10:30

地点：通达馆103会议室

主讲人简介：

        Andrea D’Ariano received the B.S. and M.S. degrees in Computer Science, Automation and Management Engineering at Roma Tre University. In November 2003, he joined TRAIL Research School and Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology. In April 2008, he successfully concluded his Ph.D. studies under the supervision of Prof. Ingo A. Hansen. In 2018 and 2022, he got the Full Professor Italian Scientific Habilitation in Operations Research and Transportation Science. He served as Expert and Rapporteur for European Commission and numerous national research foundations. Currently, he is working as Full Professor at Department of Civil, Computer Science and Aeronautical Technologies Engineering, Roma Tre University. He is the coordinator of the AIRO (Italian Association of Operations Research) Chapter on “Optimization in Public Transport and Shared Mobility”. He is Associate Editor of well-known international journals (e.g., Transportation Research Part B, C, E) and conferences (e.g., IEEE Int. Conf. on Intelligent Transportation Systems). His main research interest is the development of novel scheduling and routing methods with application to public transportation and logistics. In SCOPUS (24/9/24), he has 153 documents, 5119 citations, 41 h-index. Andrea D’Ariano is listed in the 2024 career ranking of Top 2% of the world’s best scientists (276/606 in Transportation & Logistics), compiled by Stanford University, DOI:10.17632/btchxktzyw.

主讲内容简介：

Intelligent decision support tools for aircraft monitoring and control are required in a busy Terminal Control Area (TCA). The problem of effectively managing TCA operations is particularly challenging, since there is a significant growth of traffic demand and the TCAs are becoming a bottleneck of the air traffic control system. The resulting increase in airport congestion, economic and environmental penalties can be measured in terms of performance indicators related to take-off and landing operations, e.g., aircraft delays, travel times and fuel consumption.

This talk addresses the real-time aircraft routing and scheduling problem at congested TCAs by optimizing the above-mentioned performance indicators. The mathematical formulation of this problem requires to consider the following key aspects: the aircraft trajectory and routing should be accurately predicted and optimized, the safety rules between consecutive aircraft need to be precisely modelled in each air/ground TCA resource, the aircraft timing and ordering decisions have to be taken in a short time. We discuss solving methods to integrate these modelling features and performance indicators. The proposed framework computes an initial trajectory for each aircraft, proposes a feasible aircraft schedule with pre-defined routes, and improves this schedule by rerouting some aircraft in the TCA. Computational experiments are performed on mixed-mode runway instances from Roma Fiumicino and Milano Malpensa. The disturbed traffic situations are generated by simulating multiple delayed aircraft and temporarily disrupted runways. The optimization-based approaches improve the solutions significantly compared to practical scheduling rules. However, trade-offs emerge in picking the right approach and paradigms for practical implementation..

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