What are the limitations of genetic algorithms?

What are the limitations of genetic algorithms?

Genetic algorithms have several limitations, including convergence issues, computational cost, and difficulty in handling constraints.

Can you explain the convergence issues?

Sure! Convergence issues occur when the algorithm gets stuck in local optima instead of finding the global optimum.

What about the computational cost?

The computational cost can be high, especially for complex problems, as genetic algorithms require many evaluations of the fitness function.

Are there specific types of problems where they perform poorly?

Yes, they often struggle with problems that have a large search space or require precise solutions, like certain optimization tasks.

How can these limitations be addressed?

Some strategies include hybrid approaches, adaptive genetic algorithms, and incorporating domain knowledge to improve performance.