Course - Stochastic Optimization - IØ8401
IØ8401 - Stochastic Optimization
About
This course is no longer taught and is only available for examination.
Examination arrangement
Examination arrangement: Oral examination
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| Oral examination | 100/100 | D |
Course content
The course provides knowledge of methods and models for optimization based decision support under uncertainty and risk. The course consists of three related parts:
- Theory
- Algorithms and software
- Applications in finance, production planning, energy, telecommunications among others
The course will be given next time Fall 2022.
Learning outcome
Position and function within the study program:
The course is designed for PhD students of IØT and other departments who work with theoretical and practical optimization problems in different branches of industry and services with substantial uncertainty about problem data and other elements of problem formulation. The course is built upon optimization courses in IØT's master program, knowledge of probability theory or similar knowledge.
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 will develop the following skills: Training to utilize optimization models for solution of planning and economic problems under uncertainty in energy, production, logistics, transportation, finance, telecom.
Other important learning objectives: Give training in implementation and use of relevant software for solution of optimization models under uncertainty.
Learning methods and activities
Lectures and exercises. Non-obligatory exercises. Course can be given in form of intensive lectures with several hours per day, several days per week, during limited number of weeks in semester.
Recommended previous knowledge
Master of Science, Industrial Economics and Technology Management, or similar.
Required previous knowledge
Knowledge of linear and nonlinear optimization is essential. Such knowledge can be obtained through courses TIØ4120 Basic Operations Research or TIØ4126 Optimization and Decision Support or TIØ4130 Optimization Methods or similar.
Course materials
Given at the beginning of semester.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| DIS1006 | 9.0 | ||
| IØ8804 | 3.0 | AUTUMN 2015 | |
| IØ8803 | 3.0 | AUTUMN 2016 | |
| IØ8403 | 5.0 | AUTUMN 2023 | |
| IØ8404 | 5.0 | AUTUMN 2023 |
No
Version: 1
Credits:
10.0 SP
Study level: Doctoral degree level
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: Oral examination
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Autumn ORD Oral examination 100/100 D
-
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"