What is genetic algorithm optimization?

What is genetic algorithm optimization?

Genetic algorithm optimization is a search heuristic inspired by the process of natural selection. It is used to find approximate solutions to optimization and search problems.

How does it work in practice?

In practice, it starts with a population of potential solutions. These solutions are evaluated, and the best ones are selected to create a new generation through crossover and mutation.

What are some real-world applications?

Real-world applications include scheduling, engineering design, machine learning, and even game development, where optimal solutions are crucial.

Are there any limitations to using genetic algorithms?

Yes, limitations include the potential for premature convergence, the need for careful parameter tuning, and they can be computationally expensive.