Evolutionary Algorithms

Evolutionary Algorithms are a subset of computational algorithms inspired by the principles of natural selection and biological evolution. These algorithms are used for solving optimization and search problems by mimicking the process of evolution. They typically involve a population of candidate solutions that evolve over generations through mechanisms such as selection, crossover (or recombination), and mutation.The process starts with a randomly generated population of solutions, which are evaluated based on a defined fitness function that measures their quality or performance. The best-performing solutions are selected to reproduce and create new offspring solutions. By iteratively applying these evolutionary operations, the algorithm explores the solution space, ideally converging towards optimal or near-optimal solutions over time.Evolutionary Algorithms are versatile and can be applied in various fields, including engineering, economics, artificial intelligence, and bioinformatics, making them powerful tools for tackling complex optimization problems where traditional methods may fall short.