The main inspiration of the DA algorithm originates from the static and dynamic swarming behaviours of dragonflies in nature. Two essential phases of optimization, exploration and exploitation, are designed by modelling the social interaction of dragonflies in navigating, searching for foods, and avoiding enemies when swarming dynamically or statistically.
This is the source codes of the paper:
Seyedali Mirjalili, "Dragonfly Algorithm: A New Meta-heuristic Optimization Technique for Solving Single-objective, Discrete, and Multi-objective Problems " , Neural Computing and Applications, in press, 2015, DOI: http://dx.doi.org/10.1007/s00521-015-1920-1
Link: http://link.springer.com/article/10.1007%2Fs00521-015-1920-1

If you have no access to the paper, please drop me an email at ali.mirjalili@gmail.com and I will send you the paper.

More information can be found in: http://www.alimirjalili.com/DA.html

The Matlab toolbox for this algorithm can be found here: http://au.mathworks.com/matlabcentral/fileexchange/51031-dragonfly-algorithmtoolbox

The binary version of this algorithm can be found here: http://au.mathworks.com/matlabcentral/fileexchange/51032-bda--binary-dragonfly-algorithm

The multi-objective version of this algorithm can be found here: https://au.mathworks.com/matlabcentral/fileexchange/51033-moda--multi-objective-dragonfly-algorithm

All of the source codes and extra information as well as more optimization techniques can be found in my personal website at http://www.alimirjalili.com

I have a number of relevant courses in this area. You can enrol via the following links with 95% discount:

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A course on “Optimization Problems and Algorithms: how to understand, formulation, and solve optimization problems”:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF

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