Course - Decision Modeling and Optimization - BØA2020
Decision Modeling and Optimization
Assessments and mandatory activities may be changed until September 20th.
About
About the course
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.
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 (Excel, Python),
- to transform complex models into models that are better accessible by solver software.
General Competence:
The students learns how to apply their knowledge and skills in different practical situations. They will be encouraged to reflect about advantages, shortcomings and further reaching implications of their 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
There is a mandatory coursework requirement in the course, this must be approved in order to take the exam. Further information will be given at the start of the semester.
At the exam, some or all exercises need to be implemented with Microsoft Excel.
A PC with Microsoft Excel will be provided and set up by NTNU.
The exam follows the examination regulations of NTNU.
In case of a re-sit exam or the final exam when the course is no longer being taught, the exam may be changed to an oral exam.
Specific conditions
Admission to a programme of study is required:
Business Administration (BØA)
Business Administration (BØAT)
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 |
|---|---|---|
| BØA2020 | 7.5 sp | Spring 2009 |
| BØA2020 | 7.5 sp | Spring 2009 |
| BØA2021 | 7.5 sp | Spring 2007 |
| TIØ4120 | 7.5 sp | Spring 2017 |
| TIØ4126 | 3.7 sp | Spring 2017 |
Subject areas
- Economics and Administration