Course - Advanced Stochastic Optimization - IØ8404
IØ8404 - Advanced Stochastic Optimization
About
Examination arrangement
Examination arrangement: Assignment
Grade: Passed / Not Passed
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Assignment | 100/100 |
Course content
The course provides knowledge of advanced models and methods for optimization under uncertainty. The course covers the following topics:
- Risk-averse stochastic optimization
- Distributionally robust stochastic optimization
- Mixed-integer stochastic optimization
- Stochastic optimization with endogenous uncertainty
- Implementing stochastic optimization models using appropriate software
- Applications of stochastic optimization in, e.g., energy
Learning outcome
The course is designed for PhD students who work with theoretical and practical optimization problems under uncertainty, in industry and services.
The course will convey the following knowledge: The theoretical foundation necessary for formulation, analysis and solution of stochastic programming problems and relevant applications. The knowledge necessary to conduct research in the field of optimization under uncertainty. The course builds on and extends IØ8403 Stochastic Optimization, focusing more on advanced models and software.
The course will develop the following skills: Training to build and solve optimization models for solution of planning and economic problems under uncertainty.
Learning methods and activities
Lectures and non-obligatory exercises. The course can be given in form of intensive lectures with several hours per day, several days per week, during a limited number of weeks in the semester.
Recommended previous knowledge
Knowledge of linear and nonlinear optimization is essential. Such knowledge can be obtained through courses TIØ4120 Operations Research, Introduction, TIØ4126 Optimization and Decision Support for Industrial Business Planning, or TIØ4130 Optimization Methods with Applications, or similar. The course builds on the PhD course IØ8403 Stochastic Optimization.
Required previous knowledge
Master of Science in Industrial Economics and Technology Management, or similar.
Course materials
Given at the beginning of the semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| IØ8401 | 5.0 | AUTUMN 2023 |
No
Version: 1
Credits:
5.0 SP
Study level: Doctoral degree level
Term no.: 1
Teaching semester: AUTUMN 2024
Language of instruction: English
Location: Trondheim
- Managerial Economics, Finance and Operations Research
- Industrial Economics and Technology Management
- Business Economics
- Operations Research
Department with academic responsibility
Department of Industrial Economics and Technology Management
Examination
Examination arrangement: Assignment
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
-
Autumn
ORD
Assignment
100/100
Submission
2025-01-31
INSPERA
23:59 -
Room Building Number of candidates
- * The location (room) for a written examination is published 3 days before examination date. If more than one room is listed, you will find your room at Studentweb.
For more information regarding registration for examination and examination procedures, see "Innsida - Exams"