Differential Evolution

Optimization using the evolutionary algorithm of Differential Evolution.

Description

This contribution provides functions for finding an optimum parameter set using the evolutionary algorithm of Differential Evolution. Simply speaking: If you have some complicated function of which you are unable to compute a derivative, and you want to find the parameter set minimizing the output of the function, using this package is one possible way to go.

The core of the optimization is the Differential Evolution algorithm. However, this package provides much more than the code available on the Differential Evolution homepage: http://www.icsi.berkeley.edu/~storn/code.html

Here is a list of some features:

* Optimization can run in parallel on multiple cores/computers.
* Extensive and configurable progress information during optimization.
* Intermediate results are stored for later review of optimization progress.
* Progress information can be sent by E-mail.
* Optimization toolbox is not needed.
* Quick start with demo functions.
* Intermediate results are displayed after the optimization.
* Different end conditions can be chosen (maximum time, value to reach etc.).
* Each parameter value can be constrained to an interval.
* Each parameter value can be quantized (for example for parameters of integer nature).
* Code can easily be extended to use the evolutionary algorithm of your choice.

I have developed this package for an own project. A single evaluation of my objective function took between 30 seconds and one minute and the parameter space was galactically large. If your objective function needs only milliseconds to evaluate and your optimization is expected to finish in seconds or minutes, you can still use this package. However, much of its power (parallel processing, progress notifications) will not be of much use.

Keywords: Optimization, evolutionary algorithm, genetic algorithm, differential evolution, parallel processing, distributed computing, multiple core.

• MATLAB release: MATLAB 7.3 (R2006b)
• HTML Files: differentialevolution-faq.html,; differentialevolution.html

Other Files

applause.wav,
chompsep.m,
computenewpopulation.m,
concatpath.m,
deletewithsemaphores.m,
demo1.m,
demo2.m,
demo3.m,
differentialevolution.m,
differentialevolutionslave.m,
displayerrorstruct.m,
displayoptimizationhistory.m,
existfile.c,
existfile.m,
findfiles.m,
formattime.m,
foxholes.m,
getdefaultparams.m,
gethostname.m,
getusername.m,
license.txt,
mbdatevec.m,
mbtime.m,
quantile2.m,
removefilesemaphore.m,
rosenbrocksaddle.m,
selectfigure.m,
sendmailblat.m,
setfilesemaphore.m,
tempdir2.m,
textwrap2.m,
translatedatestr.m

[Marcelo P.]

Hi Markues, This is a great submission, thanks for sharing it.

I think it is just missing documentation regarding the method, not the code. For instance, which algo are you using? did u got it from a book or a paper? If so, can you provide the reference?

[ANDREW KOH]

I think the better DE code appears at

http://www.icsi.berkeley.edu/~storn/code.html

[Markus Buehren]

As it is written in the description, exactly that code is used as the core algorithm! However, this packages offers much much more than the core algorithm.

[David Brown]

This package is unbelievably powerful. In addition Markus is always available to answer tons of questions about how to use it properly. He's even responded to fix small quirks I found in lightning fast time. This thing CHOPS hard problems to bits.

[James Yong]

One of the best optimizers I've used. The speedy support from Markus was invaluable and greatly appreciated. An amazing package. Straightforward to implement, flexible and provides results!

[Hom Gharti]

Thanks for the very very useful code. I wanted to apply this code for 4-D, 3 space dimension and 1 time dimension. I got the error 'error in bestmem ~= lastbestmem', when I checked, obviously these two vectors have different lengths, then I changed parGridVector = cell2mat(paramDefCell(:,3));
to
parGridVector = cell2mat(paramDefCell(:,4));
and code seems to be working fine. Am I doing right?

many thanks,

[STTAR WDAA]

THANK YOU VERY MUCH

[Scott]

Markus,

I think the point Andrew Koh was making is that for some reason the ")" is part of the URL in your abstract, but not in Andrew's URL, so your URL does not get to Storn's website, but Andrew's does.

Scott

[Markus Buehren]

Thanks for pointing that out, Scott. I have corrected the link.

[Olivier Desmaison]

 

[Olivier Desmaison]

Un package vraiment complet.
Un programme qui marche de suite sans avoir à retoucher quoi que ce soit. Je l'utilise pour du recalage de modèles éléments finis et ca fonctionne du tonnerre.
Bravo

[saradha devi]

helo,
based on the above comments im overwhelmed in using the code posted buy markus.ive been working on genetic algorithms n optimization toolbox for my problem on alkylation.Differential Evolution can also be applied to this prob but im not sure of how to handle the code. So could u plz give insights on how to work on it. i ve been using matlab-GA only n am a new user so i request to plz help me in dis regard.Im highly interested in workin on dis.

[James Pullen]

I'm normally way too lazy to bother rating code and submissions, but this deserves to be an exception to the rule. Very minor quibble: I'd have liked one of the demo files to have incorporated the use of external vectors/matrices. Otherwise a very concise and usable (and, more importantly, utterly useful) piece of code. Thank you Markus.

[James Pullen]

 

[Saloman Danaraj]

Very nice algorithm .I have implemented this to solve three non linear optimization problems which I will upload shrtly in the file exchange.Thank you very much.

[ardian mohib]

thank u for sharing markus, but can u tell me why when I run the codes in my computer, the codes is always error. and one more question for u, would u like to help me to explain Differential evolution algorithm. i 'm a student that interest to Differential evolution algorithm and would like to use this algorithm for solve optimization inventory supply chain for my research.
thank b4

[Mahmud Iwan]

This is an excellent code..
However, i am wondering how to use this code for constrained optimization problem (inequality constraint).?? It was given in the demo for such problem, but the code needs the initial values not to violate the constraint. in the real practice, we do not need to know whether the initial value violate it or not.Just give any initial values..right?...pls, enlighten! thanks,,