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Stochastic Fractal Search (SFS)

version 1.2 (4.85 KB) by

A novel and powerful metaheuristic algorithm that you can always rely on it

4.33333
3 Ratings

20 Downloads

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This code is the presentation of a new algorithm with new insight into solving optimization problems based on diffusion property turned up in fractals. This algorithm is able to achieve a solution that has the least (or at most, a small) error compared with the globally optimum solution within a minimal number of iterations, thus offering an improvement in terms of accuracy, convergence time and simplicity of operations.
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article link:
http://www.sciencedirect.com/science/article/pii/S0950705114002822

Comments and Ratings (5)

Hamid Salimi

Hamid Salimi (view profile)

Dear Tamara,
Would you please make me more clear about your problem. SFS algorithm is used for finding optimal parameters, and as far as I know, many researchers who work on variant fields, send me many emails about succeeding of SFS in comparison with other well-known meta heuristic algorithms in finding their optimal parameters.
Please contact me via below email:
salimi.hamid86@gmail.com

best regards,
Hamid

I tried this algorithm for the problem of fractal coding of coastlines. Unfortunately, in most cases matlab function "patternsearch" gives the better result, and is 5-6 times faster.

davoud

davoud (view profile)

What a strong algorithm with the exact results.The best one i've ever seen..

Warwick

Hamid Salimi

Hamid Salimi (view profile)

Dear all, I upload my novel metaheuristic algorithm so-called Stochastic Fractal Search (SFS)for you. I have to mention that the paper of this algorithm is under final publication process of Knowledge-Based Systems - Elsevier. The article is going to publish before Aug 2014. Therefore, to cite my article please wait until the article is published in web.

best regards,
Hamid

Updates

1.2

The first online draft of journal paper has been added. You can find it at below link:
http://www.sciencedirect.com/science/article/pii/S0950705114002822

1.1

Image has been added!

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