In this course advanced optimization methods and tools are applied to problems in the area of supply chain management. The course starts with an overview of classical combinatorial optimization problems. The course also covers the theory and application of solution methods. Concepts of exact techniques (e.g. branch and bound, branch and cut), neighborhood search and metaheuristic solution techniques (e.g. adaptive large neighborhood search, tabu search, variable neighborhood search) are discussed and implemented to solve case studies. Furthermore, hands-on exercises with standard optimization tools such as Python/PuLP and cplex are conducted.

Learning outcomes

After successful completion of the course, students should be able to

• Be familiar with the most relevant optimization models in the area of supply chain management
• Model and solve optimization problems in supply chain management
• Apply heuristic and exact solution techniques
• Analyze and solve real-world problems in selected industries and businesses

Please note that your attendance at this course must be at least 80%.

Lectures, case studies, discussion and exercises

• case study projects development and documentation (90 points)
• case study project presentations (10 points)

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