Simulated Annealing
Simulated Annealing is an optimization technique inspired by the process of heating and then slowly cooling metal to remove defects. It explores possible solutions to a problem by considering random changes, allowing poorer solutions initially to escape local optima. As the process cools, it becomes increasingly selective, focusing on better solutions. This approach helps find an approximate solution to complex problems, such as scheduling or route optimization, where traditional methods might get stuck. Essentially, it balances exploration and refinement, mimicking the natural process of cooling to reach an optimal state.
Additional Insights
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Simulated annealing is an optimization technique inspired by the process of heating and cooling metals to remove defects. Imagine a ball rolling down a hill; it seeks the lowest point representing the best solution to a problem. Initially, the ball can explore high points (less optimal solutions) to avoid getting stuck in local minima. As it "cools," it becomes less likely to jump to higher points, focusing on refining its position. This method helps find approximate solutions for complex problems in fields like engineering, scheduling, and artificial intelligence by balancing exploration and exploitation effectively.