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BDA: Binary Dragonfly Algorithm

version 1.0.0.0 (370 KB) by Seyedali Mirjalili
The binary version of the Dragonfly Algorithm (DA) for solving binary optimization problems

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Updated 22 May 2018

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This is the binary version of the recently proposed DA algorithm. 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

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Comments and Ratings (5)

eric githua

@ Pradeep: in binary optimization, the up and lb are defined by the number of bits that you allocated to your number/
@ Shimaa: because the global optimum of the objective function used is at the (0,0,0,...,0)
@ Haidy: it is fine because we add elements in this vector in the loop. However, you are correct and it would be more efficient if we first define x and then use it in the loop.

haidy

haidy (view profile)

i think there is a missing code line, that define the x data!

Shimaa Said

Why all values in result equal zero
And how I can give each solution index

pradeep

How to used binary DA for ub and lb boundary problem.

Updates

1.0.0.0

Links added:
https://www.udemy.com/optimisation/?couponCode=MATHWORKSREF
https://www.udemy.com/geneticalgorithm/?couponCode=MATHWORKSREF

1.0.0.0

Descriptions have been updated.

MATLAB Release Compatibility
Created with R2014a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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