![]() ![]() A random location for an initial solution is defined, and then for each step, a potential move to a new solution (location) is either accepted or rejected. The system has a "temperature", which controls how much change is allowed to happen. The location of each patch (x and y coordinates) can be thought of as the parameter values of the objective function. In this model, the objective function is defined for each patch in our 2D world. We use such a simple problem in this model in order to highlight the solution technique only. This model attempts to find a maximal solution in a two-dimensional grid. In simulated annealing, a minimum (or maximum) value of some global "energy" function is sought. Simulated annealing is an optimization technique inspired by the natural annealing process used in metallurgy, whereby a material is carefully heated or cooled to create larger and more uniform crystalline structures. This model demonstrates the use of a simulated annealing algorithm on a very simple two-dimensional problem. Do you have questions or comments about this model? ![]()
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