This course introduces heuristic and metaheuristic optimization methods for solving complex optimization problems that are difficult to solve exactly within reasonable computational time. The course covers constructive heuristics, local search, neighborhood design, improvement heuristics, and major metaheuristic frameworks such as simulated annealing, tabu search, genetic algorithms, variable neighborhood search, and ant colony optimization. Emphasis is placed on algorithm design principles, intensification and diversification mechanisms, parameter tuning, and computational evaluation. Students will gain both theoretical understanding and practical experience through implementation and testing on representative industrial engineering problems such as routing, scheduling, assignment, and network design.