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The document provides an in-depth analysis of Genetic Algorithms (GAs), exploring their principles, history, architecture, and applications in various fields such as engineering, finance, and machine learning. It highlights the mechanisms of GAs, including selection, crossover, and mutation, and discusses their advantages and disadvantages. The paper aims to demonstrate the effectiveness of GAs in solving complex optimization problems through a metaheuristic approach inspired by natural selection.

Author

rachaelolaonipekun544

Language

EN