Metaheuristics

Properties

• Metaheuristics are strategies that guide the search process.
• The goal is to efficiently explore the search space in order to find optimal or near–optimal solutions.
• Techniques which constitute metaheuristic algorithms range from simple local search procedures to complex learning processes.
• Metaheuristic algorithms are approximate and usually non-deterministic.
• Metaheuristics are not problem-specific. However, they were often developed in relation to a problem class such as continuous or combinatorial optimization and then generalized later in some cases.
• They can draw on domain-specific knowledge in the form of heuristics that are controlled by a higher-level strategy of the metaheuristic.
• They can contain mechanisms that prevent them from getting stuck in certain areas of the search space.
• Modern metaheuristics often use the search history to control the search.