Johan Gelinder
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Dispersive Flies Optimisation

Dispersive Flies Optimisation (DFO) is a global optimisation algorithm that is inspired by observing behaviour of swarming flies in the real world. The algorithm is going through a defined search space and it’s trying to find the most optimal value, which will converge the flies towards their target. We use the DFO to benchmark different test functions for our optimisation.

Original paper by Mohammad Majid al-Rifaie:
http://doc.gold.ac.uk/mohammad/DFO/

 In this application the “flies” are trying to find the brightest pixel in the search space. The background is affected by Perlin Noise and is constantly changing, and the agents adapts to their environment.

In this application the “flies” are trying to find the brightest pixel in the search space. The background is affected by Perlin Noise and is constantly changing, and the agents adapts to their environment.

 DFO can be used in many different image based application. In this application, the “flies” are trying to find the best position for symmetry.  They are moving randomly across the search space but always finds the middle area to be most fit.

DFO can be used in many different image based application. In this application, the “flies” are trying to find the best position for symmetry.
They are moving randomly across the search space but always finds the middle area to be most fit.