Heating and cooling the material affects both the temperature and the thermodynamic free energy or Gibbs energy. Both are attributes of the material that depend on their thermodynamic free energy. The name of the algorithm comes from annealing in metallurgy, a technique involving heating and controlled cooling of a material to alter its physical properties. For problems where finding an approximate global optimum is more important than finding a precise local optimum in a fixed amount of time, simulated annealing may be preferable to exact algorithms such as gradient descent or branch and bound. It is often used when the search space is discrete (for example the traveling salesman problem, the boolean satisfiability problem, protein structure prediction, and job-shop scheduling). Specifically, it is a metaheuristic to approximate global optimization in a large search space for an optimization problem. Simulated annealing ( SA) is a probabilistic technique for approximating the global optimum of a given function. Travelling salesman problem in 3D for 120 points solved with simulated annealing.
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