You will learn to formulate and solve optimization problems using proven methods, such as linear programming, integer programming, and nonlinear optimization. With easy-to-use Python libraries like PuLP and Pyomo, you will gain hands-on experience building models that deliver measurable value.
Designed for professionals with some background in programming and mathematics, this course will help you apply optimisation to make better, data-driven decisions in finance, supply chain, operations, and strategy. By the end, you will confidently develop and communicate optimisation solutions to support your organisation’s goals.
Key Topics:
- Day 1: Review of linear and mixed-integer linear optimisation (case study: Recharging strategy for electric vehicles)
Day 2: Network optimisation: models and heuristics (case study: Arbitrage search in cryptocurrency markets)
Day 3: Accounting for uncertainty: “Optimisation meets reality” (case study: Fleet assignment and delays)
Day 4: Robust optimisation 1 (case study: Production plan accounting for uncertainty)
Day 5: Robust optimisation 2 (case study: City routing accounting for traffic disruptions)
Day 6: Stochastic optimisation 1 (case study: distribution centre stock optimisation)
Day 7: Stochastic optimisation 2 (case study: Investment portfolio optimisation)
Day 8: Stochastic optimisation 3 (case study: Two-stage land allocation problem with uncertain yield)
Participants will leave with the skills to model, solve, and interpret complex optimisation problems in uncertain environments, gaining practical experience with cutting-edge techniques and tools.
Key Deliverables:
- Case studies to connect course concepts to real-world problems
- Daily assignments to reinforce theoretical and practical understanding
This advanced course provides participants with a comprehensive understanding of robust and stochastic optimisation, equipping them with the skills to tackle uncertainty in optimisation problems across diverse industries.
Practical programme information:
Starting dates: 31 October 2025
Tuition fee: € 4,995
Format: This course consists of 8 full days of study.
Participants are expected to work at home for 4 to 8 hours per week
Group size: 8-18
Registration deadline: 3 October 2025
(The organisation has the right to cancel or postpone the course by 3 October 2025 if there are fewer than 8 admissions)
For more information about this course, please contact: BAforIndustry@vu.nl
This course is part of the Business Analytics for Industry programme.
It includes two other courses:
