May 10, 2023 10:00 AM Singapore (Registration will open at 9:50 AM.)

Register here:
https://forms.office.com/r/XrjmBAZ1f3

Join Zoom Meeting:
https://us06web.zoom.us/j/82361720520

Meeting ID: 823 6172 0520
Passcode: 785758

Ground Delay Programs (GDPs) are crucial for air traffic flow management during capacity reductions, such as due to airport weather disruptions. The approach involves holding departing flights at collaborating airports by delaying scheduled departure times, thereby reducing costly airborne waiting at the arrival airport. This talk will highlight the potential benefits of leveraging real-time forecasts of flight arrival profiles to improve the assignment of ground delays in a dynamic and anticipative manner. An estimated 30% reduction in airborne delays is achievable with this dynamic approach in the ASEAN region compared to the static GDPs currently employed, which do not make use of arrival forecasts. We incorporate the use of real-time forecasts by modeling GDP as queueing admission control over a policy class that combines the strengths of threshold and anticipative blocking policies.

This talk is based on joint work with Satyanat Bhat, Ho Huiqi, and Divya Padmanabhan.

Paper related to the talk:
https://ieeexplore.ieee.org/document/10015468

Karthyek Murthy serves as an Assistant Professor in Singapore University of Technology & Design. His research interests lie in data-driven operations research and quantitative risk management. His research has been recognised with 2021 INFORMS Junior Faculty Forum (JFIG) Paper competition (Third place), 2019 WSC Best Paper Award, and IBM PhD fellowship. Karthyek serves as an Associate Editor for the INFORMS journal Stochastic Systems and as a judge for the INFORMS Nicholson student paper competition.

We apply the Air Traffic Flow Management (ATFM) model to a network of the ten Association of Southeast Asia Nations (ASEAN) extended to include flight information regions for Sanya and Hong Kong. We demonstrate the model’s use in capacity analysis for the region based on pre-COVID flight schedules. The sparsity of this network is revealed to create inefficiencies in response to disruption events. Of independent interest is the extension of this ATFM model to reward passenger connections (inter-tail flight connections) and consideration of scenarios which examine the issue of airline equity in passenger-centric ATFM.

Dai Gengling is a senior research assistant at the Aviation Studies Institute (ASI). Under the guidance of Professor Peter Jackson, he works on projects related to airspace network capacity problems. He graduated from the Singapore University of Technology and Design (SUTD) in 2016 with a Bachelor of Engineering (Engineering Systems and Design), with a specialisation in Financial Service and Business Analytics.

For more information about the ESD Seminar, please email esd_invite@sutd.edu.sg