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    Topic of the seminar: Introduction to Stochastic Programming and Robust Optimization
    Teacher: Fabricio Oliveira (fabricio.oliveira@aalto.fi)
    TA: Nikita Belyak (nikita.belyak@aalto.fi)

    Pre-requisites: 

    This seminar course heavily relies on the content taught in MS-E2121 - Linear Optimization. I strongly recommend having taken it before enrolling in this course. Other related courses include MS-C2105 - Introduction to Optimization; MS-E2134 - Decision Analysis (former "Decision Making and Problem Solving").

    Contents:

    The seminar offers an introduction to models and methods for optimisation under uncertainty. More specifically, we will focus on stochastic programming and robust optimization models. We will cover a range of topics related to modelling approaches, solution methods and applications.

    The exact topics to be covered depend on the number of students and will be announced later.

    Practical matters

    Seminar meetings: on Fridays 9:15 - 12:00 in room U121a (In Period II, we move to M205)

    Assessment methods: Home assignments, presentations, participation. 

    Grading principles:

    • Maximum points 100 
    1. Presentations: max 50 points - minimum requirement: presentation 'passed'
    2. Home assignments: max 30 points - minimum requirement: 15 points
    3. Participation in seminar meetings: max 6 points - minimum requirement: ~80 % of sessions attended
    4. Acting as an opponent: max 10 points - minimum requirement: completed twice
    5. Successful submission of course feedback: 4 points

    Grading scale: 0-5

    Study material: Scientific articles, book chapters, etc.

    Language of instruction: English

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