Presenter: Vaggelis Giannikas Date: 15 May 2019
Abstract: Air transportation systems are exposed to daily disruptions, which have significant impact on operations causing not only monetary loss, but also customer dissatisfaction. Airlines operate tight schedules to maximise resource utilisation. However, the lack of sufficient buffers often result in the domino effect, where a delay of a single flight can delay many other dependent flights. Due to the complexity of air transportation systems the task of identifying the cause of a delay is not trivial. In this paper, we propose a framework for automatic detection of root-causes of delays and their propagation effects using airline historical data. The framework is composed of the following: 1) delay propagation model to create connection network, 2) delay network algorithm to find delay networks, and 3) community detection algorithm to identify root-causes and impact of disruptions. We test our framework on historical data of an airline, and show that the airline under study is prone to delay propagation through passenger connections. Additionally, majority of their delays are related to airport capacity, resource allocation, and passengers, and mainly originate from the hub.
Short bio: Dr Vaggelis Giannikas is an Associate Professor at the School of Management, University of Bath where he also directs the engineering management teaching portfolio. He is studying the development and evaluation of intelligent logistics systems with applications in manufacturing, warehousing, inventory management and airline networks. A significant part of Vaggelis's research has been conducted in collaboration with corporations in Europe, USA and China. Prior to joining the University of Bath, Vaggelis served as a research associate at the Institute for Manufacturing, University of Cambridge where he was also the associate director of the Cambridge Auto-ID lab. He holds a PhD in Operations Management and Technology from the University of Cambridge and a BSc in Management Science and Technology from the Athens University of Economics and Business.