Evolutionary Algorithms are optimization techniques inspired by the process of natural selection. They mimic biological evolution by using mechanisms such as selection, mutation, and crossover to evolve solutions to complex problems. These algorithms start with a population of potential solutions and iteratively improve them over generations. The main goal of Evolutionary Algorithms is to find the best solution among many possibilities. They are widely used in various fields, including artificial intelligence, engineering, and economics, to solve problems that are difficult for traditional methods. By exploring a diverse set of solutions, they can effectively navigate complex solution spaces.