Login for PhD students/staff at UCPH      Login for others
3rd Copenhagen School of Stochastic Programming
Provider: Faculty of Science

Activity no.: 5577-26-00-00There are 59 available seats 
Enrollment deadline: 30/04/2026
PlaceDepartment of Mathematical Sciences
Date and time22.06.2026, at: 00:00 - 26.06.2026, at: 16:00
Regular seats60
LecturersTrine Krogh Boomsma
ECTS credits2.50
Contact personNina Weisse    E-mail address: weisse@math.ku.dk
Enrolment Handling/Course OrganiserPhD Administration SCIENCE    E-mail address: phdcourses@science.ku.dk
Enrolment guidelines
This is a specialised course where 50% of the seats are reserved to PhD students enrolled at the Faculty of SCIENCE at UCPH and 50% of the seats are reserved to other applicants. Seats will be allocated on a first-come, first-served basis and according to the applicable rules.

Anyone can apply for the course, but if you are not a PhD student at a Danish university (except CBS), you will be placed on the waiting list until enrollment deadline. After the enrollment deadline, available seats will be allocated to applicants on the waiting list.


Aim and Content
This course provides a rigorous and research-oriented introduction to stochastic programming, a mathematical framework for decision-making in the presence of uncertainty. In many real-life problems, important parameters are unknown to the decision-maker and only distributional information is available. Examples include the scheduling of power generation under uncertainty in renewable supply, investments in assets with uncertain future returns or production of goods for which demand is stochastic. The purpose of the course is to prepare the students for carrying out independent research, including developments and applications of the methodology.

The days of the course will be divided into a morning and an afternoon session. During the morning session, the course will host lectures by world-renowned scientists on the subject. During the afternoon sessions, the students will have a chance of presenting their own work and discuss their research challenges between themselves and with the experts.

A plan of the activities is as follows (the order may change):
• Day 1: - Morning: Formalization of decision problems under uncertainty as stochastic programs. Brief account of the main mathematical properties (speaker: Trine Boomsma, KU).
• Day 1 – Afternoon: First round of student presentations (in progress) on stochastic programming.
• Day 2 – Morning: Introduction scenario generation (speaker: Stein Wallace, Norwegian School of Economics)
• Day 2 – Afternoon: Second round of student presentation (in progress) on stochastic programming.
• Day 3 – Morning: Chance-constrained stochastic programming (speaker: Miguel Lejeune, George Washington University)
• Day 3 – Afternoon: Third round of student presentations (in progress) on stochastic programming.
• Day 4 – Morning: Introduction to multi-stage models (speaker: Steffen Rebennack, Karlsruhe Institute of Technology)
• Day 4 – Afternoon: Fourth round of student presentation (in progress) on stochastic programming.
• Day 5 – Morning: Stochastic programs with endogenous uncertainty (speaker: Giovanni Pantuso, KU)
• Day 5 – Afternoon: Fifth round of student presentations (in progress) on stochastic programming.


Learning outcomes
Intended learning outcome for the students who complete the course:

Knowledge:
• Formulations of two-stage, multi-stage and chance-constrained stochastic programming problems, possibly with endogenous uncertainty
• Properties of stochastic programming problems
• Solution and approximation methods

Skills:
• Formulate different types of stochastic programming problems, depending on the interplay between decision-making and information disclosure, on the required probability of feasibility, and on the relationship between uncertainty and decisions
• Approximate the uncertain data by means of scenarios
• Develop solution strategies for different types of stochastic programming problems

Competences:
• Recognize and structure a decision problem affected by uncertainty and propose a suitable mathematical formulation
• Identify a suitable way of representing or approximating the uncertain data of the problem and its effect on decisions
• Devise appropriate solution methods for the decision problem
• Quantify and analyze the impact of uncertainty on the decision problem and its solution


Target Group
PhD students from e.g., mathematics, engineering, economics, working with optimization under uncertainty.


Recommended Academic Qualifications
Linear programming and probability theory.


Research Area
Optimization and decision-making.


Teaching and Learning Methods
• Self-study before and during the course.
• 3 hours of lectures per day for 5 days.
• 4 hours of student presentations per day for 5 days.
• Final assignment.


Type of Assessment
The students will be assessed based on an assignment to be delivered after the end of the course.


Literature
J. R. Birge and F. Louveaux (2011) Introduction to Stochastic Programming.
Selected research papers.


Course coordinator
Trine Krogh Boomsma (Professor)


Guest Lecturers
TBA


Dates
June 22-26, 2026.


Course location
HCØ, Nørre Campus




Course fee
• Participant fee: 800 DKK
• PhD student enrolled at SCIENCE: 0 DKK
• PhD student from Danish PhD school Open market: 0 DKK
• PhD student from Danish PhD school not Open market: 3000 DKK
• PhD student from foreign university: 3000 DKK
• Master's student from Danish university: 0 DKK
• Master's student from foreign university: 3000 DKK
• Non-PhD student employed at a university (e.g., postdocs): 3000 DKK
• Non-PhD student not employed at a university (e.g., from a private company): 8400 DKK

Cancellation policy
• Cancellations made up to two weeks before the course starts are free of charge.
• Cancellations made less than two weeks before the course starts will be charged a fee of DKK 3.000
• Participants with less than 80% attendance cannot pass the course and will be charged a fee of DKK 5.000
• No-show will result in a fee of DKK 5.000
• Participants who fail to hand in any mandatory exams or assignments cannot pass the course and will be charged a fee of DKK 5.000

Course fee and participant fee
PhD courses offered at the Faculty of SCIENCE have course fees corresponding to different participant types.
In addition to the course fee, there might also be a participant fee.
If the course has a participant fee, this will apply to all participants regardless of participant
type - and in addition to the course fee.

Search
Click the search button to search Courses.


Course calendar
See which courses you can attend and when
JanFebMarApr
MayJunJulAug
SepOctNovDec



Publication of new courses
All planned PhD courses at the PhD School are visible in the course catalogue. Courses are published regularly.