What is simulated annealing?

What is simulated annealing?

Simulated annealing is an optimization technique inspired by the annealing process in metallurgy. It helps find a good approximation to the global optimum of a given function.

How does it work?

It works by exploring the solution space and allowing occasional uphill moves to escape local minima, gradually reducing the probability of such moves as the process continues.

What are its applications?

Simulated annealing is used in various fields, including operations research, artificial intelligence, and engineering, for problems like scheduling, routing, and circuit design.

Is it better than other optimization methods?

It depends on the problem. Simulated annealing is often more effective for complex landscapes, but other methods like genetic algorithms or gradient descent may perform better in different scenarios.

Can you give an example of a problem it solves?

Sure! A classic example is the traveling salesman problem, where it helps find the shortest possible route that visits a set of cities.