Amsterdam, Netherlands

Operations Research: A Mathematical Way to Optimize Your World

when 17 July 2021 - 31 July 2021
language English
duration 2 weeks
credits 3 EC
fee EUR 850

NOTE: Given the insecurity about the development of covid-19 and its influence on on-campus (offline) activities, all –then applicable- guidelines from the Dutch government will be followed. On 1 May, we will decide whether this course can run on-campus or if we will have to cancel it.

Nowadays, everyone is talking about the tremendous opportunities offered by “big data” and all kinds of analytics. To really make the difference, though, you need to be able to turn data and analytical insights into better managerial decisions – and that requires rigorous quantitative tools.

This course delivers those tools, introducing you to the most successful models and algorithms from operations research (OR), including (integer) linear optimization, network optimization, stochastic optimization and heuristics. Not only do you learn some of the beautiful but basic mathematics behind them, but during computer practicals you gain hands-on experience with up-to-date software applied to practical cases in such domains as logistics and revenue management. The course will enable you to recognize and exploit opportunities for mathematically supported decision making and can help prepare you for an MSc in Operations Research.

Specific topics include:

• The world of optimization, considering both deterministic and stochastic problems (that is, with and without data uncertainty).
• Modelling optimization problems using powerful tools such as integer programming.
• Some insights into the theory that drives the effectiveness of these tools.
• The use of optimization software, such as Matlab, Python, and Gurobi.
• Algorithms for key problems in network optimization, such as finding the cheapest tour through a network.
• Understanding stochastic processes like Markov chains to model uncertainty in operational systems.
• Queueing models and queueing networks.
• Stochastic dynamic programming techniques to determine optimal decisions in operational problems.
• Stochastic computer simulation techniques, enabling you to model and analyse realistic problems in operational systems.

Course leader

Dr A. A. N. Ridder, Dr D. A. van der Laan, Dr R. A. Sitters, Prof. L. Stougie

Target group

Students and professionals in the field of Engineering, Computer Science, Physics, Mathematics or Quantitative Business Studies. Our courses are multi-disciplinary and therefore are open to students and professionals with a wide variety of backgrounds.

Course aim

At the end of this course, you:
•Can model a practical optimization problem into an appropriate mathematical formulation.
•Can solve the mathematical model using advanced optimization software.
•Have a knowledge of network optimization problems and the algorithms to solve them.
•Have a knowledge of optimization theory and integer linear programming techniques
•Can model uncertainty in operational systems as a stochastic process.
•Can simulate a stochastic process using simulation software.

Credits info

3 EC
Contact Hours: 45
Do you want to make the most out of your summer? You can combine this course with a course in session 1 to create a 4-week Summer School in Amsterdam.

Fee info

EUR 850: The tuition fee of a two-week course depends on your situation and ranges from €850-1150. This tuition fee includes:
- Two week course;
- Exclusive content for a limited number of students;
- Transcript of records with a maximum of 3 ECTS (European study credits);
- Certificate of attendance after completing the course;
- Individual/group guidance from professor;
- Interactive classes;
- Full support from the summer school team;
- For on-campus courses: airport pick-up and welcome activities.

Scholarships

VU Amsterdam Summer School offers three kinds of scholarships: the Academic Scholarship, the Photographer Scholarship and the Vlogger/Videographer Scholarship. More information can be found on the VU Amsterdam Summer School website.

Register for this course
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