Here you will find the lectures that are offered during the summer term.
If you would like to attend a seminar or if you are interested in doing your bachelor's or master's thesis at our chair, please contact
Dr. habil. Mahdi Moeini,
Dr. Hagen Salewski, or
Daniel Schermer to receive information about available topics.
- Operations Research 1:
- Introduction to Operations Research: planning models and methods.
- Networks, graphs, and their applications: Paths in graphs, networks, flows in graphs, transportation problem
- Linear Optimization: basic model structures, Simplex algorithm, special LP structures, different phases of Simplex, variables with lower and upper bounds, post-optimality analysis (sensitivity analysis), parametric optimization, applications and modeling, duality.
- Integer linear optimization: Examples and case studies, Branch & Bound, Cutting Planes.
- Stochastic Processes: Queueing theory, simulation of stochastic processes.
- Operations Research 2:
- Nonlinear Optimization: Unconstrained and constrained nonlinear problems and models, Convex optimization, Karush-Kuhn-Tucker-conditions, lagrangian method, Quadratic optimization (Wolfe’s Algorithm), approximation methods (Golden Section, Gradient Method), Barrier methods, Penalty methods.
- Heuristics: problem search methods (A*-algorithm), local search methods, Simulated Annealing, Genetic Algorithms.
- This block course demonstrates the implementation of operational processes in the standard software SAP ERP by means of case studies.
- Starting points are the models and optimization approaches exemplified in "Business Process Management".
- Characteristics of Multi-Agent Systems
- Intelligent Agent and System Architectures
- Agent Communication and Ontologies
- Distributed planning, problem solving, and learning methods in Multi-Agent Systems
- Simulation, game theory and economic aspects of Multi-Agent Systems.
- Industrial applications: Multi-Agent Systems in logistics, supply-chain management and IT resource management.
- Design and prototypical implementation of solution methods with Mutli-Agent Systems.
- Tasks will be given by the chair and concern supply-chain management (trading agent competition), coordination of service networks, logistics, or others.
- A short report and presentation of results is required.
- Easy versus hard optimization problems
- Problem Space Search: A*-algorithm
- Solution Space Search: local search, simulated annealing, tabu search, variable neighborhood search
- Population-based Search: genetic algorithms, artificial ants, swarm optimization
- Modeling and Programming
- Initiation to programming with Python
- Mathematical modeling
- Initiation to solver Gurobi
- Bayesian Belief Networks
- Cooperative Simulated Annealing
- Reinforcement Learning, supervised and unsupervised learning, ...
- Artificial Neural Networks
- Yield Management
The lectures take place as a block during June 24-27, 2019 in 42-421a.
The exact schedule of each day will be announced as soon as it becomes ready.
Printed lecture slides as well as some pdf files and source codes will be provided during the lectures.
- Classification of Logistic Systems
- Logistic Demand Analysis
- Logistic Network Design
- Location Problems
- Inventory Management
- Warehouse design and management
- Short-Haul Transportation