The technology that uses the principles of genetics to solve optimization problems is known as genetic algorithms. These algorithms mimic the process of natural selection, evolving solutions to problems over successive iterations. By using techniques inspired by biological evolution, such as selection, crossover, and mutation, genetic algorithms can effectively explore large search spaces, identifying optimal or near-optimal solutions in various fields, including engineering, finance, and artificial intelligence. Their ability to adapt and improve over time makes them a powerful tool in complex problem solving.