What are the advantages of simulated annealing?
Simulated annealing is beneficial for solving complex optimization problems as it can escape local minima.
Can you explain how it works?
Sure! It mimics the cooling process of metals, gradually reducing the temperature to find a global optimum.
What types of problems is it best suited for?
It's particularly effective for combinatorial problems, like the traveling salesman problem and scheduling.
Are there any limitations to using it?
Yes, it can be slow and may require careful tuning of parameters to achieve optimal results.
How does it compare to other optimization methods?
Simulated annealing is often more flexible than gradient descent, especially in non-convex landscapes.
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