Discussing the article: "Population optimization algorithms: Intelligent Water Drops (IWD) algorithm"
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Published article Population-based Optimisation Algorithms: Intelligent Water Drops (IWD) Algorithm:
Author: Andrey Dik
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Check out the new article: Population optimization algorithms: Intelligent Water Drops (IWD) algorithm.
IWD is a model, in which water drops find the optimal path to their destination by changing the course of a river. This is facilitated by three important parameters. Due to their own speed, drops are able to capture soil from the bottom of the river. The higher the speed, the greater the amount of soil each drop can carry with it, respectively, the freer the path becomes for subsequent agents. The flow rate increases where there is no soil to clear. The optimal path is the one containing the least amount of soil where the highest speed can be reached. With the help of IWD, it is possible to implement an optimization strategy where random agents intelligently interact with each other in such a way that they jointly change the course of the river and create an optimal path, in which no soil is encountered at all and the flow rate of the agents becomes the highest possible.
Basic principles:

In nature, many drops of water are observed in rivers, where they form huge masses (swarms of water drops). The paths, along which natural rivers flow, were created by swarms of water drops. Swarms of water drops (rivers) are part of the environment that has been significantly modified by the swarm and is also subject to change in the future. Moreover, the environment itself has a significant influence on the paths of water drops. They face the resistance of river banks. For instance, a swarm of water drops is resisted more by those parts of the environment that make up hard soil than by parts that make up soft soil. The natural course of a river is the result of competition between water drops and the environment, which resists their movement.Author: Andrey Dik