Program Overview

Course Overview

The course Advanced Stochastic Optimization (Iﾘ8404) is a doctoral degree level course that provides knowledge of advanced models and methods for optimization under uncertainty.

Course Details

• Credits: 5
• Level: Doctoral degree level
• Course start: Autumn 2025
• Duration: 1 semester
• Language of instruction: English
• Location: Trondheim
• Examination arrangement: Assignment

About the Course

Course Content

The course covers the following topics:

• Risk-averse stochastic optimization
• Distributionally robust stochastic optimization
• Mixed-integer stochastic optimization
• Stochastic optimization with endogenous uncertainty
• Implementing stochastic optimization models using appropriate software
• Applications of stochastic optimization in, e.g., energy

Learning Outcome

The course is designed for PhD students who work with theoretical and practical optimization problems under uncertainty, in industry and services. The course will convey the theoretical foundation necessary for formulation, analysis, and solution of stochastic programming problems and relevant applications. It will also provide the knowledge necessary to conduct research in the field of optimization under uncertainty.

Learning Methods and Activities

The course includes lectures and non-obligatory exercises. It can be given in the form of intensive lectures with several hours per day, several days per week, during a limited number of weeks in the semester.

Requirements and Recommendations

Recommended Previous Knowledge

Knowledge of linear and nonlinear optimization is essential. Such knowledge can be obtained through the courses TIﾘ4120 Operations Research, Introduction, TIﾘ4126 Optimization and Decision Support for Industrial Business Planning, or TIﾘ4130 Optimization Methods with Applications, or similar. The course builds on the PhD course Iﾘ8403 Stochastic Optimization.

Required Previous Knowledge

Master of Science in Industrial Economics and Technology Management, or similar.

Course Materials and Credit Reductions

Course Materials

Course materials are given at the beginning of the semester.

Credit Reductions

The course has academic overlap with Iﾘ8401. If you take overlapping courses, you will receive a credit reduction in the course where you have the lowest grade. If the grades are the same, the reduction will be applied to the course completed most recently.

Subject Areas

• Managerial Economics, Finance and Operations Research
• Industrial Economics and Technology Management
• Business Economics
• Operations Research

Examination

The examination arrangement for the course is an assignment, with a weighting of 100/100. The assignment is submitted through the Inspera Assessment exam system.