Hi, I am Nils Löhndorf! I am an Associate Professor at the Luxembourg Centre for Logistics and Supply Chain Management within the University of Luxembourg and Chairholder in Digital Procurement. As researcher and entrepreneur, I help decision-makers to make better in decisions in the face of uncertainty.
My research interest is in developing approximate dynamic programming methods and models for decision-making under uncertainty. In recent years I have developed a range of models for operation, valuation, and trading of energy storage systems that are used by several energy companies in Europe.
Based on my research on stochastic optimization, I have developed a general-purpose solver for stochastic-dynamic optimization called QUASAR. The solver is intended for analysts, decision-makers, and researchers who want to solve difficult sequential decision problems that involve uncertainty. You can use QUASAR to solve linear multistage stochastic programs, continuous Markov decision processes, or stochastic-dynamic programs. QUASAR features
QUASAR provides native interfaces for Python and Java. If you want to try QUASAR go to quantego.com and sign up for a free trial. QUASAR is entirely free for academic usage.
Click here to generate scenarios from a multivariate distribution (normal, log-normal, uniform) for Monte Carlo simulation, numerical integration or stochastic programming. The generator is based on experiments with different scenario generation methods which are described in this article. The code is available on GitHub.