Discussing the article: "Artificial Bee Hive Algorithm (ABHA): Tests and results"
Check out the new article: Artificial Bee Hive Algorithm (ABHA): Tests and results.
Author: Andrey Dik
Hi Andrew. I've known about this algorithm for over 10 years, and it was considered one of the best in the ant algorithm family.
The results are below expectations. regards
Hi Andrei. I have known about this algorithm for more than 10 years, and it was considered one of the best in the ant algorithm family.
The results were lower than expected. with respect.
Hi. Yes, it does happen. For example, the same PSO turns out to be much weaker than one thinks it is. There are also situations when developers claim overestimated search capabilities of their algorithms, but in practice it turns out to be otherwise. This is one of the goals of my articles - to provide true and reproducible results of the most well-known optimisation algorithms.
There are several variations of algorithms on the theme of "bees", this one is one of the strongest among them.
Hi. Yes, it does happen. For example, the same PSO turns out to be much weaker than one thinks it is. There are also situations when developers claim overestimated search capabilities of their algorithms, but in practice it turns out to be otherwise. This is one of the goals of my articles - to provide true and reproducible results of the most well-known optimisation algorithms.
There are several variations of algorithms on the theme of "bees", this one is one of the strongest among them.
the Ans (Across Neighbourhood search) is like the cream of the crop
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Check out the new article: Artificial Bee Hive Algorithm (ABHA): Tests and results.
In this article, we will continue exploring the Artificial Bee Hive Algorithm (ABHA) by diving into the code and considering the remaining methods. As you might remember, each bee in the model is represented as an individual agent whose behavior depends on internal and external information, as well as motivational state. We will test the algorithm on various functions and summarize the results by presenting them in the rating table.
In the previous article we delved into the fascinating world of the Artificial Bee Hive Algorithm (ABHA) by thoroughly examining its operating principles. We described the structure and class, as well as presented the algorithm pseudocode together with the Moving and Revision methods. This introduction will form the basis for further study and understanding of the algorithm.
In this article, we will continue delving into coding and covering all the remaining methods. As always, we will conduct testing on various test functions to evaluate the efficiency and performance of the algorithm. In conclusion, we will summarize the results of the algorithm work in the rating table.
Author: Andrey Dik