Prof. Dr. Nils Löhndorf

Nils Löhndorf is Chair Holder in Digital Procurement and Associate Professor at the Luxembourg Centre for Logistics and Supply Chain Management (LCL).

Nils's research interests are in operations research, in particular optimization under uncertainty, with current applications in operational management and valuation of energy storage systems.

Nils has published his research in leading journals like Operations Research, European Journal of Operational Research, and IIE Transacations.

Energy companies in Austria, Germany, and Italy actively use Nils's models for operation and valuation of energy storage systems, like reservoirs of hydropower plants and natural gas storages, as well as virtual power plants.

Prior to joining LCL, Nils was an assistant professor at Vienna University of Economics and Business, Austria, where he received his Habilitation in Business Administration in 2017.

Last updated on: mardi 13 décembre 2022

MSc Level

2017 - 2018, Analytical Methods and Data Science, University of Luxembourg, Master in Logistics and Supply Chain Management

2014 - 2017, Data Mining and Decision Support Systems, WU Vienna, MSc Information Systems

2013 - 2014, Advanced Operations Research, WU Vienna, MSc Supply Chain Management

2012 - 2014, Advanced Planning Systems, WU Vienna, MSc Information Systems

2010, International Logistics, University of Vienna, MSc Business Administration

2008 - 2012, Simulation II, University of Vienna, MSc Business Administration

BSc Level

2015 - 2016, Process Management Tools, WU Vienna, BSc Business Administration

2012 - 2015, Operational Planning, WU Vienna, BSc Business Administration

2013 - 2016, Methods of Information Systems Research, WU, BSc Information Systems
 

Last updated on: 12 nov 2018

Nils vision is to develop models that help decision-makers to make better decisions in the face of uncertainty and to foster the use of stochastic-dynamic optimization in practice. Current research projects are:

• optimal dynamic hedging of natural gas storage contracts when markets are incomplete;
• optimal bidding strategies for storages and flexible capacity in short-term markets for electricity;
• strategic capacity planning of production networks when there is substantial uncertainty about long-term sales forecast;
• empirical analysis of methods for multistage stochastic programming, in particular approximate dynamic programming and scenario-tree based stochastic programming.

Last updated on: 25 mai 2018

Löhndorf N, Shapiro A. 2017. Modeling time-dependent randomness in stochastic dual dynamic programming. Available on Optimization Online.

Löhndorf N, Wozabal D. 2017. Indifference pricing of natural gas storage contracts. Available on Optimization Online.

Löhndorf N. 2016. An empirical analysis of scenario generation methods for stochastic optimization. European Journal of Operational Research 255(1), 121-132.

Löhndorf N, Riel M, Minner S. 2014. Simulation optimization for the stochastic economic lot scheduling problem with sequence-dependent setup times. International Journal of Production Economics 157, 170-176.

Löhndorf N, Wozabal D, Minner S. 2013. Optimizing trading decisions for hydro storage systems using approximate dual dynamic programming. Operations Research 61, 810-823.

Löhndorf N, Minner S. 2013. Simulation optimization for the stochastic economic lot scheduling problem. IIE Transactions 45, 796-810.

Transchel S, Minner S, Kallrath J, Löhndorf N, Eberhard U. 2011. A hybrid general lot-sizing and scheduling formulation for a production process with a two-stage product structure. International Journal of Production Research 49(9), 2463-2480.

Francas D, Löhndorf N, Minner S. 2011. Machine and labor flexibility in manufacturing networks. International Journal of Production Economics 131(1), 165-174.

Löhndorf N, Minner S. 2010. Optimal day-ahead bidding with renewable energies and storage. Energy Systems 1(1), 61-77.

Last updated on: 25 mai 2018