Generic Algorithms

Genetic Algorithms are problem-solving techniques inspired by the process of natural selection. They simulate the way living organisms evolve over time. In this method, potential solutions to a problem are treated like individuals in a population. The algorithm combines and modifies these solutions—similar to breeding—through processes like selection, crossover, and mutation. Over multiple generations, the algorithm gradually improves the solutions, allowing it to find more effective answers to complex problems. This approach is often used in optimization tasks, such as in engineering, scheduling, and artificial intelligence, where traditional methods may struggle.