![]() This is because simulated annealing allows for small changes to be made to the solution, which means that it can escape from local minima and find the global optimum. The advantage of simulated annealing over other optimization methods is that it is less likely to get stuck in a local minimum, where the solution is not the best possible but is good enough. In the same way, simulated annealing can be used to find solutions to optimization problems by slowly changing the values of the variables in the problem until a solution is found. It is based on the idea of annealing in metallurgy, where a metal is heated and then cooled slowly in order to reduce its brittleness. Simulated annealing is a technique used in AI to find solutions to optimization problems. ![]()
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