  | ZLATANOVA, K.* , SIEBENTRITT, S.* , SCHULZ, C.* , FRIDGEN, G., HANSEN, J., LÖHNDORF, N., MANTIN, B., Pontenciano Menci, S., SCHYMANSKI, E., & VENDITTI, S. (2024). RISK2050: study on the vulnerability of the national economy in the face of physical risks. * These authors have contributed equally to this work. |
  | Seranilla, B. K., & Löhndorf, N. (2023). Optimizing vaccine distribution in developing countries under natural disaster risk. Naval Research Logistics. doi:10.1002/nav.22143  Peer Reviewed verified by ORBi |
 | Löhndorf, N., & Wozabal, D. (January 2021). Gas Storage Valuation in Incomplete Markets. European Journal of Operational Research, 288 (1), 318-330. doi:10.1016/j.ejor.2020.05.044 Peer Reviewed verified by ORBi |
 | Löhndorf, N., & Wozabal, D. (2021). The Value of Coordination in Multimarket Bidding of Grid Energy Storage. Operations Research. doi:10.1287/opre.2021.2247 Peer Reviewed verified by ORBi |
 | Avila, D., Papavasiliou, A., & Löhndorf, N. (2021). Parallel and distributed computing for stochastic dual dynamic programming. Computational Management Science. doi:10.1007/s10287-021-00411-x Peer Reviewed verified by ORBi |
 | Löhndorf, N. (2021). Dynamic Hedging for the Real Option Management of Hydropower Storage Operations with Exchange Rate Risks. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/46060. |
 | Avila, D., Papavasiliou, A., & Löhndorf, N. (2021). Batch Learning in Stochastic Dual Dynamic Programming. ORBilu-University of Luxembourg. https://orbilu.uni.lu/handle/10993/49798. |
 | Löhndorf, N., & Shapiro, A. (2019). Modeling time-dependent randomness in stochastic dual dynamic programming. European Journal of Operational Research, 273 (2), 650--661. doi:10.1016/j.ejor.2018.08.001 Peer reviewed |
 | Dimoski, J., Nersten, S., Fleten, S.-E., & Löhndorf, N. (2018). Hydropower reservoir management using multi-factor price model and correlation between price and local inflow. In Hydropower reservoir management using multi-factor price model and correlation between price and local inflow. International Association for Energy Economics. Peer reviewed |
 | Löhndorf, N. (2016). An empirical analysis of scenario generation methods for stochastic optimization. European Journal of Operational Research, 255 (1), 121--132. doi:10.1016/j.ejor.2016.05.021 Peer reviewed |
 | 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. doi:10.1016/j.ijpe.2014.05.006 Peer reviewed |
 | Löhndorf, N., & Minner, S. (2013). Simulation optimization for the stochastic economic lot scheduling problem. IIE Transactions, 45 (7), 796--810. doi:10.1080/0740817X.2012.662310 Peer reviewed |
 | Löhndorf, N., Wozabal, D., & Minner, S. (2013). Optimizing Trading Decisions for Hydro Storage Systems using Approximate Dual Dynamic Programming. Operations Research. doi:10.1287/opre.2013.1182 Peer Reviewed verified by ORBi |
 | Francas, D., Löhndorf, N., & Minner, S. (2011). Machine and labor flexibility in manufacturing networks. International Journal of Production Economics, 131 (1), 165--174. doi:10.1016/j.ijpe.2010.03.014 Peer reviewed |
 | 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. doi:10.1080/00207543.2010.532910 Peer reviewed |
 | Löhndorf, N., & Minner, S. (2010). Optimal day-ahead trading and storage of renewable energies—an approximate dynamic programming approach. Energy Systems, 1 (1), 61--77. doi:10.1007/s12667-009-0007-4 Peer reviewed |