IØ8403 - Stochastic Optimization


New from the academic year 2023/2024

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 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

Learning outcome

Position and function within the study programme:

The course is designed for PhD students of the Department of Industrial Economics and Technology Management (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 programme, knowledge of probability theory or similar knowledge.

The course will covey 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. 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.

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
More on the course



Version: 1
Credits:  5.0 SP
Study level: Doctoral degree level


Term no.: 1
Teaching semester:  AUTUMN 2023

Language of instruction: English

Location: Trondheim

Subject area(s)
  • Managerial Economics, Finance and Operations Research
  • Industrial Economics and Technology Management
  • Business Economics
  • Operations Research
Contact information
Course coordinator: Lecturer(s):

Department with academic responsibility
Department of Industrial Economics and Technology Management


Examination arrangement: Assignment

Term Status code Evaluation Weighting Examination aids Date Time Examination system Room *
Autumn ORD Assignment 100/100 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"

More on examinations at NTNU