randomized search heuristics

Randomized search heuristics are methods used to find good solutions to complex problems by exploring possibilities unpredictably. Instead of following a strict step-by-step plan, they introduce randomness in selecting actions or modifications, helping to avoid getting stuck in suboptimal solutions. These techniques are useful for difficult optimization tasks, such as scheduling or design, where exact methods are too slow or impractical. By sampling a wide range of options randomly, they increase the chance of discovering high-quality solutions efficiently. Examples include algorithms like simulated annealing and genetic algorithms, which balance exploration and exploitation through randomness.