Discussing the article: "Chaos Game Optimization (CGO)"
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Check out the new article: Chaos Game Optimization (CGO).
Imagine a group of researchers, each trying to find an extremum in a multidimensional labyrinth. At the beginning of the journey, our seekers are scattered randomly throughout the labyrinth and find their first refuge within strictly defined boundaries of space. This is their starting point. Each seeker does not act alone - he observes his peers, and at any given moment, he selects a random group of peers, calculates the center of their location, as if finding a point of balance between their positions.
It is the collective wisdom, averaged over the group's experience. And then the real magic of chaos begins. The seeker can choose one of four paths for his next step. Each path is a special equation of movement, where three key points are intertwined: seeker's current position, the best place found by the whole group, and the center of the selected subgroup. These points are mixed, and the strength of their influence on further movement is determined by the α ratio – the conductor of chaos.
The α ratio itself takes on different incarnations, and each seeker, following the rules, can either push off from his position, rushing towards the golden mean between the best result and the center of the group, or start from the best point, exploring the space around it, and can also push off from the center of the group, or make a completely random leap into the unknown.
At the end of each such action, a comparison of the results takes place. If one of the seekers finds a place better than the previous record, it becomes a new beacon for the entire group in their further search.
This is the true beauty of the algorithm - its ability to transform chaos into order, randomness into purposeful movement, uncertainty into progress, and every step, every movement is subordinated to the search for solutions between the known and the unknown, between stability and risk, between order and chaos.
Author: Andrey Dik