Tabu Search is a metaheuristic that guides local search procedures to explore solution spaces beyond local optimality. It maintains a tabu list - a short-term memory of recently visited solutions or moves to prevent cycling. Key components: (1) neighborhood structure defining candidate moves; (2) tabu list storing forbidden moves for a tenure period; (3) aspiration criteria allowing tabu moves if they lead to best-known solutions; (4) intensification strategies to search promising regions thoroughly; (5) diversification strategies to explore new regions. Advanced features include: long-term memory, strategic oscillation, and path relinking. Applications include: scheduling, routing, facility location, and telecommunications network design.