metaheuristiline

Metaheuristiline is a Finnish term that translates to "metaheuristic" in English. Metaheuristics are high-level algorithmic frameworks that provide a set of guidelines or strategies to develop heuristic optimization algorithms. They are designed to find a good enough solution to an optimization problem, especially when exact methods are too slow or impossible to implement due to the problem's complexity.

Unlike heuristics that are tailored to a specific problem, metaheuristics are general-purpose and can be adapted to a wide range of optimization problems. They typically involve mechanisms to explore the search space and escape local optima. Common examples of metaheuristics include genetic algorithms, simulated annealing, tabu search, and ant colony optimization.

These methods are often used in fields such as computer science, operations research, and artificial intelligence for problems like scheduling, routing, and machine learning. The goal is not necessarily to find the absolute best solution but rather a solution that is of high quality and can be found within a reasonable amount of time. The "meta" in metaheuristic signifies that it operates at a higher level of abstraction, guiding the design of specific heuristic methods.