global optimization techniques

Global optimization techniques are methods used to find the best possible solution to a problem among many options. Imagine trying to find the lowest point in a hilly landscape—these techniques explore different paths and areas to identify the absolute lowest point, rather than just a local dip that might not be the lowest overall. They are used in areas like engineering, finance, and machine learning to effectively solve complex problems where multiple solutions exist, ensuring the most optimal outcome is achieved across the entire solution space.