Stochastic programming and robust optimisation

This notes are the lecture notes of the course MS-EXXXX, taught at Aalto University, Department of Mathematics and Systems Analysis since 2023.

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Course content:

Introduction to stochastic programming

• 1. The farmer’s problem
• 2. Two-stage stochastic programming
• 3. Measuring the quality of 2SSP solutions
• 4. Types of recourse
• 5. Multi-stage stochastic programming (MSSP) problems

Uncertainty representation in stochastic programming

• 6. Using scenarios for representing uncertainty
• 7. Quality measures for scenario trees
• 8. Scenario (tree) generation methods
• 9. Sample average approximation

Chance constraints and risk measures

• 10. Chance constraints
• 11. Risk measures

Robust optimisation

• 12. Robust optimisation
• 13. Adjustable robust optimisation

• Bibliography