Seminar: Optimization models for Air Traffic Flow Management by Sadeque Hamdan

Department of Industrial Engineering 

Optimization models for Air Traffic Flow Management
Sadeque Hamdan

Post-doctoral Researcher at the United Arab Emirates University


Delays and emissions are critical topics in the aviation industry. The major delay sources are imbalanced demand and capacity, air traffic controller staffing, and severe weather conditions. In some cases, flights can choose to fly at a higher speed than the scheduled one, which increases emissions. Moreover, several projects have been initiated to improve information sharing, and consequently, decision making in order to benefit all aviation parties and reduce delays and emissions. In this work, we study the air traffic flow management (ATFM) problem from an operations research/operations management perspective. We extend the network design and the considered features to reach a better representation of the real-life network. In this extension, we consider several types of flights and several decision options. The proposed models help decision-makers fine-tune and verify findings of several ATFM projects and initiatives. They also suggest to decision-makers how flight plans can be updated in cases of network disturbance and the associated costs of the changes.


Sadeque Hamdan is a Post-doctoral Researcher at the United Arab Emirates University. He holds a Ph.D. degree in Complex Systems Engineering from CentraleSupelec, Universite Paris-Saclay, France. He also has a master's degree in Engineering Management and a bachelor's degree in Civil Engineering from the University of Sharjah, UAE. Before joining the United Arab Emirates University, Sadeque Hamdan has worked for almost four years as a full-time research assistant at the Sustainable Engineering Asset Management Research Group, University of Sharjah, UAE. His research areas include air traffic management, supply chain management, routing, and maritime transportation.   

Date: Friday, April 30, 2021


Online Seminar Link:

Meeting ID: 934 3051 2540

Passcode: 335899