Master

Supply chain and operations management are key factors for a company to be competitive on a global market. Aim of the course is to introduce students to problems arising in supply chain management and operations management and make them familiar with traditional and recent approaches to address and solve these problems. The course is structured in 6 weekly units. Introductory basics and simple tutorials are provided online for self-study. Advanced topics, case studies, and the broader context will be discussed in classroom. Participation in the classroom meetings is strongly recommended, because many relevant topics will be discussed there. The grading will be based on the best 3 out of 5 online tests in Moodle and a 90 min. exam during the exam week. The tests will always be at the end of the week, starting from Sunday 18:00 and ending Monday 18:00, last for 15 minutes and you can gain 15 points. The final test will be 65 points worth. So the maximum you can reach is 110 points.  A minimum of 50 points overall, 15 points for the online quizzes and 25 points for the final test are necessary to pass the course.

This is an advanced course about mixed integer programming (MIP) as a tool for planning and optimizing in operations management. MIPs are one of the most widely used concepts to model decision problems in management. In this course we will look behind the curtain and identify easy and not so easy problem classes, model various decision problems, discuss ways to solve the problems mainly with the help of Python and Gurobi. Gurobi is one of the market leader of software tools for solving MIPs. Commercial licenses for this software costs thousands of euros. In this course you have the chance to learn how to use this software. Prerequisites: Completed course Introduction to Operations Research (basic knowledge of linear and mixed integer programs, Python and Gurobi) The course Data Analysis and Visualization with Python is also helpful but not required. There is a limit of 15 participants. Participants are accepted according to their grade in the courses Methods of Information and Operations Management or Introduction to Operations Research .  The course will be held as an mixed on-campus and online course. We will provide videos, scripts and other material here in Moodle and we will have meetings on Tuesday 17-20 in GD 202 and Thursday 14-16 in HG 104 starting from May 6th. Topics of the course are: Relaxations, bounds, branch & bound Cutting planes Lagrangian Duality Column generation MIP-based heuristics MIP model in operations management Implementations in Python/Gurobi The grading will be based on online-quizzes in Moodle, assignments (implementation in Python/Gurobi), presentations, and oral exam and short seminar reports.

This is an advanced course about the concepts of Metaheuristics and their implementation in Python. Metaheuristics are advanced algorithms for generating high-quality solutions for complex optimization problems. The have similarities with machine learning algorithms, because they are adapting themselves automatically to the given optimization problem. We will use Python as programming language to implement simple versions of well-known state-of-the-art metaheuristics for various planning problems. Prerequisites: Basic knowledge in Python (completed course Introduction to Operations Research or Data Analysis and Visualization with Python) There is a limit of 15 participants in total. Participants are accepted according to their grade in the courses Introduction to Operations Research or Data Analysis and Visualization with Python.  The course will be held in a blended learning format in classroom and online. We will provide videos, scripts and other material here in Moodle. We have (more or less regularly) weekly meetings on Wednesday 13:30-16 in AM 204 or online starting from May 6th. Topics of the course are: Introduction to Python and Jupyter Notebook Basic ideas of metaheuristics The concept of local search algorithms Local-search-based metaheuristics Population-based metaheuristics The grading will be based on online-quizzes in Moodle, assignments (implementation of Metaheuristics in Python), presentations, an oral exam and short seminar reports.

Qualification objective: The participants will learn about the basics of the classic network design and transportation problems and the impact of sustainability notion on these problems, in particular, we will discuss environmental and social impacts, alternative fuel vehicles and new logistics problems based on the sustainability concept. Additionally, we will look at new transportation vehicles especially uncrewed (autonomous) vehicles and their applications. Requirements for participation: Good knowledge and deep interest in logistics systems, operations research and mathematical modelling. Course dates: 2nd block.

THE APPLICATION FOR THIS COURSE IS CLOSED

Unfortunately, this course cannot take place this semester and has been canceled! We apologize for any inconvenience this may cause!

Application submission deadline: Monday, 7th of April 2025, 12 noon via Moodle https://moodle.europa-uni.de -LS Marketing (Prof. Brunk) (Bewerbungsverfahren)

Please read the course description on the moodle webpage