Discussing the article: "Population optimization algorithms: Simulated Isotropic Annealing (SIA) algorithm. Part II"
I get the impression that we have witnessed the transition of quantity (skills/knowledge) to quality (improved algorithms).
On the test FFs it's impressive, thanks! Need FFs in the form of TCs.
The impression is that we have witnessed a transition of quantity (skills/knowledge) to quality (improved algorithms).
On the test FFs it's impressive, thanks! Need FFs in the form of TCs.
Thanks for the feedback.
I randomly pick algorithms to investigate and improve them if I see an opportunity. So, there are many modified algorithms in the table that I have improved, it's just that this one had more potential for improvement than others. Of course, that experience accumulates, but turning SA into SIA was obvious and I couldn't help but do it.
As for the trading test FF, you can use the benchmark described here. There is a selection of theoretical knees of the zigzag so that the maximum possible number of points of "profit" would be obtained.
By the way, it would be necessary to formalise UGA in the current OOP-format and include it in the table. As soon as I get my hands on it, I will do it. I have no doubt it will take its place in the upper part of the table. I will not write an article about him again, I will just add him to the archive together with the rest of his colleagues.
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There are several ways to implement both external optimisation control and internal self-optimisation of Expert Advisors, including without using dll. There are several articles by other authors on this topic.
I have a separate article with examples of how to screw AO to an Expert Advisor under development.
How to apply these algorithms for trading or optimisation ? There is a test Expert Advisor MACD Sample. We would describe how to apply all of these developments for this Expert Advisor
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Check out the new article: Population optimization algorithms: Simulated Isotropic Annealing (SIA) algorithm. Part II.
The first part was devoted to the well-known and popular algorithm - simulated annealing. We have thoroughly considered its pros and cons. The second part of the article is devoted to the radical transformation of the algorithm, which turns it into a new optimization algorithm - Simulated Isotropic Annealing (SIA).
The results are impressive. Besides, the number of parameters have decreased by one.
Visualization of the algorithm operation demonstrates a clear division into separate clusters of agents with all significant local extrema covered. The image resembles the actual crystallization of solidifying metal. We can clearly see the excellent convergence on all tests, including the ones with many variables.
SIA on the Rastrigin test function
Author: Andrey Dik