Discussing the article: "Camel Algorithm (CA)"

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Check out the new article: Camel Algorithm (CA).

The Camel Algorithm, developed in 2016, simulates the behavior of camels in the desert to solve optimization problems, taking into account temperature, supply, and endurance. This article also presents a modified version of the algorithm (CAm) with key improvements: the use of a Gaussian distribution in generating solutions and the optimization of the oasis effect parameters.

In recent decades, a significant number of optimization algorithms have emerged that are inspired by natural phenomena and animal behavior. These bio-inspired approaches have shown excellent results in many tasks. In this article, we will examine a new optimization algorithm called the Camel Algorithm (CA), based on the survival and movement strategies of camels in extreme desert conditions. The algorithm was developed and presented in 2016 by two scientists: Mohammed Khalid Ibrahim and Ramzy Salim Ali.

Camels have unique physiological characteristics and behavioral adaptations that allow them to effectively navigate and survive in harsh desert environments with limited resources, extreme temperatures, and changing landscapes. The CA algorithm models key aspects of this behavior: the influence of temperature, management of water and food supplies, endurance, the effect of "oases" (promising search areas), as well as group interaction in the caravan.

As usual, we will analyze the original algorithm's internals, modify it, and test both versions on test functions. The results will be included in our optimization algorithm ranking table.


Author: Andrey Dik

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