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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.
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