Discussing the article: "African Buffalo Optimization (ABO)"

New comment
 

Check out the new article: African Buffalo Optimization (ABO).

The article presents the African Buffalo Optimization (ABO) algorithm, a metaheuristic approach developed in 2015 based on the unique behavior of these animals. The article describes in detail the stages of the algorithm implementation and its efficiency in finding solutions to complex problems, which makes it a valuable tool in the field of optimization.

The African Buffalo Optimization (ABO) algorithm is a metaheuristic approach inspired by the remarkable behavior of these animals in the wild. The ABO algorithm was developed in 2015 by scientists Julius Beneoluchi Odili and Mohd Nizam Kahar based on the social interactions and survival strategies of African buffaloes.

African buffalo are known for their ability to defend themselves in groups and for their coordination in finding food and water. These animals live in large herds, which provides them with protection from predators and helps them form tight groups where adults take care of the young and weak. When attacked by predators, buffalo demonstrate impressive coordination skills: they can form a circle around vulnerable members of the herd, or attack the enemy with a joint effort.

The basic principles of the ABO algorithm reflect key aspects of buffalo behavior. First, communication: the buffaloes use sound signals to coordinate their actions, which in the algorithm corresponds to the exchange of information between agents. Second, learning: buffaloes learn from their own experiences and the experiences of other herd members, which is implemented in the algorithm by updating the agents' positions based on the information collected.


Author: Andrey Dik

 
Very interesting article.
Thank you Andrew for your hard work and contribution.
Looking forward to your articles with optimisation methods of Jumping Grasshoppers and Attack Panther.
 

The author is very good! As an absolute "dummy" in this topic, I am just amazed at how many different methods of optimisation there are. Probably with pearl buttons too? ))

Andrei, can you tell me please, in what software was the visualisation (for example ABO on the Forest test function) performed? Maybe it was mentioned somewhere, but I missed it....

Next article about Indian elephants or Mexican tushkans? ))

 
Nikolai Semko #:
Very interesting article.
Thank you Andrei for your labour and contribution.
Looking forward to your articles with optimisation methods of Jumping Grasshoppers and Attack Panther.

Thank you, Nikolay, for your kind words.

I haven't heard anything about the Jumping Grasshoppers algorithm, but there seem to be some on the topic of cats: Panther Optimisation Algorithm (POA) and Mountain Lion Algorithm (MLA). Might be considered by me if I can find a description sufficient to reproduce the logic of these search strategies.

 
Denis Kirichenko #:

The author is very good! As an absolute "dummy" in this topic, I am just amazed at how many different methods of optimisation there are. Probably with pearl buttons too? ))

Andrei, can you tell me please, in what software was the visualisation (for example ABO on the Forest test function) performed? Maybe it was mentioned somewhere, but I missed it....

Next article about Indian elephants or Mexican tushkans? ))

Thanks, Denis.

I use only MQL5 language in my articles on mql5.com, the visualisation is built in MT5 using standard tools. All source codes are available in the attachment to the article and you can reproduce my results.

 
Some of my articles have hidden "passphrases" in them, but so far none have been found by readers.
New comment