19 August 2017
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 prepare you for an MSc in Operations Research.
Specific topics include:
• The world of optimization theory, considering both deterministic and stochastic problems (that is, with and without data uncertainty).
• Modelling deterministic optimization problems as (integer) linear programs or convex programs.
• The use of optimization software, such as Matlab, Python, and Gurobi.
• Algorithms for basic network optimization problems, such as finding an optimal flow, matching or tour in a network.
• Integer programming and combinatorial optimization theory.
• Stochastic processes modelling the uncertainty in operational systems (Markov chains, Poisson processes, Brownian motion).
• Queueing models and queueing networks.
• Stochastic dynamic programming techniques to determine optimal designs 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 of Engineering, Computer Science, Physics, Mathematics or Quantitative Business Studies.
• You can model a practical optimization problem into an appropriate mathematical formulation.
• You can solve the mathematical model using advanced optimization software.
• You have a knowledge of network optimization problems and the algorithms to solve them.
• You have a knowledge of optimization theory and integer linear programming techniques
• You can model uncertainty in operational systems as a stochastic process.
• You can simulate a stochastic process using simulation software.
45 contact hours
EUR 1000: Included in the tuition fee are:
• Airport pick-up service
• Orientation programme
• Course excursions
• On-site support
• 24/7 emergency assistance
• Transcript of records after completion of the course
Early bird discount of €100 for anyone who applies before 1 March 2017. €250 discount for students from partner universities. Ten scholarships available that cover the full tuition fee of one course. For more info please check our website.Register for this course
on course website