Robustness and evolutionary dynamic optimisation of airport security schedules

Date

2017-06

Advisors

Journal Title

Journal ISSN

ISSN

DOI

Volume Title

Publisher

Springer

Type

Conference

Peer reviewed

Yes

Abstract

Reducing security lane operations whilst minimising passenger waiting times in unforseen circumstances is important for airports. Evolutionary methods can design optimised schedules but these tend to over-fit passenger arrival forecasts resulting in lengthy waiting times for unforeseen events. Dynamic re-optimisation can mitigate for this issue but security lane schedules are an example of a constrained problem due to the human element preventing major modifications. This paper postulates that for dynamic re-optimisation to be more effective in constrained circumstances consideration of schedule robustness is required. To reduce over-fitting a simple methodology for evolving more robust schedules is investigated. Random delays are introduced into forecasts of passenger arrivals to better reflect actuality and a range of these randomly perturbed forecasts are used to evaluate schedules. These steps reduced passenger waiting times for actual events for both static and dynamic policies with minimal increases in security operations.

Description

Keywords

Airport security lane scheduling, Robust dynamic optimisation, Evolutionary algorithm

Citation

Chitty, D.M., Yang, S. and Gongora, M. (2017) Robustness and evolutionary dynamic optimisation of airport security schedules. Proceedings of 23rd International Conference on Soft Computing (MENDEL 2017), pp. xxx-xxx

Rights

Research Institute

Institute of Artificial Intelligence (IAI)