Now showing items 1-6 of 6
Ant colony optimization for simulated dynamic multi-objective railway junction rescheduling
Minimising the ongoing impact of train delays has benefits to both the users of the railway system and the railway stakeholders. However, the efficient rescheduling of trains after a perturbation is a complex real-world ...
Considering flexibility in the evolutionary dynamic optimisation of airport security lane schedules
Airports face pressures to reduce costs at the security lane area by reducing lane opening hours whilst maintaining a passenger service level. Evolutionary methods have been shown to design schedules that minimise both ...
Finding multi-density clusters in non-stationary data streams using an ant colony with adaptive parameters
(IEEE Press, 2017-06)
Density based methods have been shown to be an effective approach for clustering non-stationary data streams. The number of clusters does not need to be known a priori and density methods are robust to noise and changes ...
Evolutionary dynamic optimisation of airport security lane schedules
Reducing costs whilst maintaining passenger satisfaction is an important problem for airports. One area this can be applied is the security lane checks at the airport. However, reducing costs through reducing lane openings ...
Ant colony stream clustering: A fast density clustering algorithm for dynamic data streams
(IEEE Press, 2018-03-30)
A data stream is a continuously arriving sequence of data and clustering data streams requires additional considerations to traditional clustering. A stream is potentially unbounded, data points arrive on-line and each ...
Robustness and evolutionary dynamic optimisation of airport security schedules
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 ...