11 August 2018
on course website
Operations Research: A Mathematical Way to Optimize Your World
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.
Dr A. A. N. Ridder, Dr D. A. van der Laan, Dr R. A. Sitters, Prof. L. Stougie
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.
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.
Contact Hours: 45
If you want to earn more credits you can take courses in our other sessions to create a 4 or 6 week programme.
EUR 1000: The tuition fee includes:
• Airport pick-up service
• Welcome goodie bag
• Orientation programme
• Course excursions
• On-site support
• Emergency assistance
• Transcript of records after completion of the course
An early bird discount of €150 is available for students who apply and pay before 15 March, and students from VU Amsterdam as well as from exchange partner universities will receive a €250 discount. You apply for the discount simply by indicating that you are currently a student at VU Amsterdam or at a partner university in the online application.
There are also discounts for students who attend multiple sessions, combine 2 courses and receive a €200 discount and combine 3 to receive a €300 discount. All courses include excursions. We will also organize trips and excursions as part of our social programme, which is a great way to get to know your fellow students and learn more about Amsterdam and the Netherlands. The social programme is not included in the tuition fee.
Furnished accommodation is available. Various housing options will be offered.
The VU Amsterdam Summer School offers ten scholarships that cover the full tuition and housing fees of one course. Information about how to apply for the scholarship will be posted on the VU Amsterdam Summer School website.Register for this course
on course website