Discussing the article: "Bacterial Chemotaxis Optimization (BCO)"
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Check out the new article: Bacterial Chemotaxis Optimization (BCO).
The article presents the original version of the Bacterial Chemotaxis Optimization (BCO) algorithm and its modified version. We will take a closer look at all the differences, with a special focus on the new version of BCOm, which simplifies the bacterial movement mechanism, reduces the dependence on positional history, and uses simpler math than the computationally heavy original version. We will also conduct the tests and summarize the results.
Various studies have found that bacteria exchange information with each other, although not much is known about the mechanisms of this communication. Typically, bacteria are treated as individuals and social interactions are not taken into account in models. This distinguishes them from interaction models describing the behavior of social insects (such as ants, bees, wasps, or termites), which act as systems with collective intelligence, which opens up different possibilities for solving various problems.
Adaptation is another important aspect of chemotaxis. Bacteria are able to change their sensitivity to constant chemical conditions, allowing them to respond effectively to changes in the environment. This quality makes them not only hardy, but also highly efficient in finding resources.
In this study, the authors focused on microscopic models that account for the chemotaxis of individual bacteria, as opposed to macroscopic models that analyze the movement of colonies. The algorithm was developed by S. D. Müller and P. Koumatsakas, and its main ideas were presented and published in 2002.
Author: Andrey Dik