course-details-portlet

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

Compulsory activities from previous semester may be approved by the department.

Admission to a programme of study is required:
Business Administration (BØA)
Business Administration (ØABACHELOR)

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
More on the course

No

Facts

Version: C
Credits:  7.5 SP
Study level: Third-year courses, level III

Coursework

Term no.: 1
Teaching semester:  SPRING 2023

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Economics and Administration
Contact information
Course coordinator:

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.
Examination

For more information regarding registration for examination and examination procedures, see "Innsida - Exams"

More on examinations at NTNU