Course - Decision Modelling and Optimization - BØA2020
BØA2020 - Decision Modelling and Optimization
About
Examination arrangement
Examination arrangement: School exam
Grade: Letter grades
| Evaluation | Weighting | Duration | Grade deviation | Examination aids |
|---|---|---|---|---|
| School exam | 100/100 | 4 hours | A |
Course content
The following topics are taught in this course:
- Linear optimization (graphical method, Simplex method, sensitivity analysis and duality)
- Integer programming (Branch and Bound)
- Network models (transport, transshipment, travelling salesman, shortest path and similar models)
- Non-linear optimization (with/without constraints, gradient descent method, KKT conditions)
- Decision tree model
- Introduction to dynamic optimization and reinforcement learning.
Most of the models will be implemented by means of Excel spreadsheets and Excel solver.
Learning outcome
Knowledge: The student
- learns about the variety of practical decision problems that can be described by means of quantitative models.
- receives knowledge about necessary components and properties of quantitative decision models.
- obtains knowledge about solution methods or algorithms that are useful to find solutions to decision problems and models.
Skills: The student will be enabled
- to translate practical decision problems into quantitative models
- to analyze the properties of decision models
- to apply appropriate methods for finding solutions to decision models,
- to implement decision models with software,
- to transform complex models into models that are better accessible by solver software.
General Competence:
The student learns how to apply his knowledge and skills in different practical situations. He will be encouraged to reflect about advantages, shortcomings and further reaching implications of his models and solutions.
Learning methods and activities
Lectures (physical or digital), videos, written exercises and data exercises.
Compulsory assignments
- To obligatoriske innleveringer
Further on evaluation
At the exam, some or all exercises need to be implemented with Microsoft Excel.
The exam follows the examination regulations of NTNU.
In case of postponed examination (continuation examination), written examination may be changed to oral examination.
Specific conditions
Admission to a programme of study is required:
Business Administration (BØA)
Economics and Business Administration (MSIVØK5)
Required previous knowledge
This course requires elementary courses in mathematics and managerial economics.
Course materials
The curriculum will be announced when the course commences.
Credit reductions
| Course code | Reduction | From | To |
|---|---|---|---|
| BØA2020 | 7.5 | SPRING 2009 | |
| BØA2020 | 7.5 | SPRING 2009 | |
| BØA2021 | 7.5 | SPRING 2007 | |
| TIØ4120 | 7.5 | SPRING 2017 | |
| TIØ4126 | 3.7 | SPRING 2017 |
No
Version: C
Credits:
7.5 SP
Study level: Third-year courses, level III
Term no.: 1
Teaching semester: SPRING 2025
Language of instruction: English
Location: Trondheim
- Economics and Administration
Department with academic responsibility
NTNU Business School
Examination
Examination arrangement: School exam
- Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
- Spring ORD School exam 100/100 A INSPERA
-
Room Building Number of candidates - Summer UTS School exam 100/100 A INSPERA
-
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"