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Finding the Global Minimum of a Function using Simulated Annealing

POSTED BY: Housam Binous
10 Replies

I am tied up with other stuff. Eventually, I will get to it. Please use my Email to contact me. Best regards, Housam

POSTED BY: Housam Binous

thanks, I have received the code and I will have a look at it the coming days

POSTED BY: Housam Binous

Hi Housam,

Minimize and NMinimize are known to give global solution unless some warning was given. You can find this stated in the "Details and Options" section of their documentation pages.

Which version of Mathematica are you using?

Using V13.3 I get the global solution by both

POSTED BY: Ahmed Elbanna

I am using v.12. Thanks for the info

POSTED BY: Housam Binous

This is true of Minimize. But NMinimize can get trapped in a local min. In this example of course it does just fine:

In[109]:= NMinimize[f[x], x, Method -> "SimulatedAnnealing"]

Out[109]= {-3.0233, {x -> -0.711232}}

Also one should bear in mind that any method based on simulated annealing can get trapped. It just doesn't happen for this example and the implementations presented.

POSTED BY: Daniel Lichtblau
Posted 9 months ago

Hi Housam,

That is a great job. Congratulations.

Archimedes optimization algorithm is a new and most useful in engineering. I have its code in Matlab, but I would like to have it in Mathematica. I am new in Mathematica and don't have experience for providing it code. I know you are so busy, so may I ask you to do that in Mathematica?

Best Regards, Alex

POSTED BY: Alex Teymouri

thanks. OK kindly share AOA Matlab coding with me and I will do it using MATHEMATICA

binoushousam@yahoo.com

POSTED BY: Housam Binous
Posted 9 months ago

Dear Housam,

the AOA code in Matlab has been sent to your email address.

Regards

POSTED BY: Alex Teymouri
Posted 8 months ago

Hi Housam,

I attached herewith the AOA source code.

Thank you .

Attachments:
POSTED BY: Alex Teymouri
Posted 8 months ago

Dear Housam,

Have you received the AOA files?

Looking forward to hearing your reply.

POSTED BY: Alex Teymouri
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