Copenhagen School of Stochastic Programming
International PhD School,
University of Copenhagen
4-8 April 2022
The Copenhagen School of Stochastic Programming is a PhD course that 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 information is unknown to the decision-maker and only distributional information is available. Examples include the scheduling of power generation while demand and renewable production are uncertain, investments in assets with uncertain future returns or production of goods for which demand is stochastic.
The course is taught by world-renowned experts on the subject (see below). It will start by formalizing decision problems under uncertainty as mathematical optimization problems and analyzing their fundamental mathematical properties. From a computational perspective, these problems may be extremely challenging. Thus, a major part of the course will discuss approximations, mainly of the underlying probability distributions (so-called scenario generation), and stability of the optimization problems. The course will then proceed with a number of applications in the energy sector, an area in which stochastic programming has become increasingly important with the adoption of intermittent renewable energy sources. Finally, a selection of solution methods will be addressed, including exact decomposition procedures and approximate methods with strong connections to emerging approaches in machine learning.
The course is primarily aimed at PhD students who require a solid introduction to decision making under uncertainty. Nevertheless, it is open to anyone who would like to approach the subject, ranging from master's students to more experienced researchers and professionals. A participant can earn a certificate of 3.5 ECTS upon successful completion of the course. The course is open to students from all over the world and the registration is free.
- 14th March: Registrations have now been completed. We have registered a number of students from the waiting list up to the available capacity. Students currently in the waiting list will unfortunately not be able to attend.
- Due to the extraordinary high number of students already signed up we had to close registrations on February 14. This is to make sure that we can accommodate all participants. Nevertheless, we are keeping a waiting list (see Registrations below). Students in the waiting list will be informed shortly after March 4th if any additional place has become available.
- The course will be held in Auditorium 1 which is situated in the H.C. Hørsted building. See directions below. It is not possible to attend the event online.
- There will be a dinner on April 7th. The dinner is optional and requires a contribution of 275 DKK. See Social Events below.
The course will be taught by the following experts on stochastic programming. In order of appearance in the course:
- Stein W. Wallace is a Professor of Operational Research and leader of the Centre for Shipping and Logistics at NHH. He is best known for his seminal work in stochastic programming -- in particular the two books Stochastic Programming (with Peter Kall from 1994) and Modeling with stochastic programming (with Alan King from 2012) -- but also for extensive work in logistics and energy systems. His work has received more than 10.000 citations. He is on numerous editorial boards, in particular INFORMS Journal on Computing (since 1990), and founded the Norwegian OR Society and has held elected positions in The British OR Society as well as The Society for Transportation and Logistics in INFORMS and The Mathematical Programming Society.
- Mike Hewitt is a Professor in the Information Systems and Supply Chain Management Department in the Quinlan School of Business at Loyola University Chicago. His research includes developing quantitative models of decisions found in the transportation and supply chain management domains, particularly in freight transportation and home delivery. In this research he has developed cutting-edge techniques for solving complex stochastic programs. His work has assisted the decision-making of companies such as Exxon Mobil, Saia Motor Freight, and Yellow Roadway. His research has been funded by agencies such as the National Science Foundation, the Material Handling Institute, and the New York State Health Foundation.
- Stein-Erik Fleten is a Professor of Operations Research at the Norwegian University of Science and Technology. His work is centered mainly around the development of models of energy markets, such as power scheduling and risk management. In addition his research produces reference applications of stochastic programming for investment under uncertainty. Fleten is currently Editor-in-chief of Computational Management science, one of the most prestigious journals focusing on stochastic optimization research. His work appears regularly in the leading operations research and energy scientific journals. He is a broadly recognized energy expert in the stochastic programming community.
- David Wozabal is a Professor at the Technical University of Munich. His research deals with the development of algorithms for stochastic optimization problems, risk measurement and risk management. The impressive theoretical results of his research are successfully applied to crucial planning problems in energy management as well as classical problems in finance such as portfolio optimization. His research focuses on the structural problems of the European energy markets with particular regard to electricity markets. A major part of this work involves modeling price processes and examining the efficiency of electricity markets. The results of this research are of central importance for the entire European energy sector.
The students will become well acquainted with the theory of stochastic programming and the challenges involved when applying stochastic programming in practice. Particularly, upon completion of the course, the students will be able to formulate two-stage and multi-stage stochastic programs, analyze their properties and discuss their practical implications. They will also learn how to approximate these problems, generate scenarios and address stability with respect to these, bound and assess the value of stochastic optimization. Finally, they will be able to apply and adapt selected traditional and novel solution methods.
Prerequisites for a successful participation in the course are a solid understanding of linear programming theory and some knowledge of probability theory (e.g., understanding what probability distributions are for both continuous and discrete random variables). Knowledge of a linear/mixed-integer programming solver is also beneficial.
This is the schedule of the PhD School's activities. Each day is led by an international expert on Stochastic Programming and consists of circa two hours of lectures and three hours of exercises or project work on the same topic.
|Monday April 4th|
|10:00-10:15||Welcome session and introduction to the PhD course|
|10:15-12:00||Trine K. Boomsma: An Introduction to Stochastic Programming|
|14:00-16:00||Stein W. Wallace: Scenarios in Stochastic Programming|
|Tuesday April 5th|
|10:00-12:00||Stein W. Wallace: Scenarios in Stochastic Programming -- exercises and discussion on a few practical cases|
|14:00-15:30||Stein W. Wallace: Scenarios in Stochastic Programming -- concluding discussion and input on student's cases|
|15:30-16:00||Mosek: Presentation of Mosek solver|
|Wednesday April 6th|
|10:00-12:00||Mike Hewitt: Benders decomposition strategies for two-stage stochastic programs|
|14:00-17:00||Mike Hewitt: Benders decomposition strategies for two-stage stochastic programs -- practical cases|
|Thursday April 7th|
|10:00-12:00||Stein-Erik Fleten: Energy forward contracts: Fundamental aspects and Stochastic Programming uses|
|14:00-17:00||Stein-Erik Fleten: Energy forward contracts: Fundamental aspects and Stochastic Programming uses -- group exercises and discussion|
|18:00-21:00||Course social dinner
|Friday April 8th|
|10:00-12:00||David Wozabal: Approximate Dynamic Programming and Stochastic Dual Dynamic Programming|
|14:00-17:00||David Wozabal: Approximate Dynamic Programming and Stochastic Dual Dynamic Programming -- experiments on a practical case|
There will be a course dinner on Thursday April 7th 18.00-21.00. The participation at the dinner has a cost of 275 DKK that helps us to cover the corresponding expenses. Below you find a registration link also for the dinner. Please register before March 4th.
The course will be taught physically at the department of mathematical sciences. Lectures might be recorded but remote attendance is not allowed.
However, the ongoing coronavirus pandemics dictates some additional precautions when traveling and paying attention to the rules enforced by the arrival and departure countries. You can find updated entry rules for Denmark at this dedicated website.
As of January 2022, traveling to Denmark from EU/Schengen countries, requires a negative tests performed 2-3 days before departure, while additional requirements might be enforced when traveling from outside EU/Schengen.
We advise participants to keep themselves informed at the website provided as the rules tend to change periodically. We hope, and expect, the rules will be less strict as we approach Spring.
Registration is now closed
Soon after March 4th we will contact you to inform you if any place has become available.
In order to obtain an ECTS certificate, the participant needs to:
- Attend the lectures
- Deliver a short essay on the topics of the course
Upon request the organizers may provide letters of invitation for the purpose of obtaining a visa. In order to obtain a letter of invitation the following conditions must hold:
- The student must have registered for the course (not on the waiting list)
- The request arrives from an institutional email (requests from personal emails will be discarded)
- The student must provide proof of enrollment in a PhD program and a request of participation at the course written by the PhD supervisor.