The course starts with an overview of different optimization methods and techniques applied in logistics, and software review. The following optimization methods are considered in the course: Mathematical Programming (Linear Programming (LP), Integer Programming (IP), and Dynamic Programming); Numeric Optimization (Tree/Graph Search methods – Branch & Bound); Heuristic Optimization and Metaheuristics (Greedy, Tabu, Simulated Annealing, Genetic Algorithms, Evolutionary Strategy); Constraint Programming and Simulation-based Optimization. In the practical part of the course different optimization algorithms are applied to benchmark optimization problems in logistics by using the heuristic optimization environments and simulation-based optimization software tools, and a case study in logistics optimization is developed in groups.