Discussing the article: "Chaos optimization algorithm (COA): Continued"
It is surprising to see that when the different methods are combined it generates a kind of static as those of the old televisions, and that like her in a certain way this showing a kind of "noise" or chaos that remains recorded in yes, must be by the same fact of as the small initial variations determined by the sensitivity end up altering totally the final result, in truth that we are insignificant, very good article.
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Check out the new article: Chaos optimization algorithm (COA): Continued.
In the previous article, we introduced the chaotic optimization method and analyzed some of the methods included in the algorithm. In this article, we will complete the analysis of the remaining methods and move directly to testing the algorithm on test functions.
In this implementation, the chaotic optimization method uses deterministic chaos to explore the solution space. The key principle is the use of three different chaotic maps (logistic, sinusoidal and tent maps) to generate sequences that have pseudo-randomness and ergodicity properties. The algorithm operates in three phases: an initial chaotic search, a solution refinement using the weighted gradient method, and a final local search with adaptive scope narrowing.
I would like to draw attention to the visualization of the algorithm operation: the combination of the variety of search methods used produces an unusual visual effect.
Author: Andrey Dik