Hi, I am Nils Löhndorf, and 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 are in stochastic optimization, in particular approximate dynamic programming, and its application to decision problems that involve uncertainty as they often occur in operations management.
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
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.