Metaheuristics are high-level problem-solving frameworks designed to generate solutions for complex optimization problems that are difficult to solve with traditional methods. They combine elements of heuristics and optimization techniques, enabling them to explore large search spaces effectively while balancing exploration and exploitation. These methods are particularly useful in addressing problems like combinatorial optimization, where finding an exact solution may be impractical due to time or computational constraints.
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