Now showing items 21-23 of 23
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 ...
A benchmark test suite for evolutionary many-objective optimization
In the real world, it is not uncommon to face an optimization problem with more than three objectives. Such problems, called many-objective optimization problems (MaOPs), pose great challenges to the area of evolutionary ...
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 ...