Frauke Liers at AAAI-24!
We are delighted to announce that Frauke’s research, has been successfully accepted at the 38th Annual AAAI Conference on Artificial…
Prof. Dr. Frauke Liers
Department of Data Science (DDS)
Professorship of Optimization under Uncertainty & Data Analysis (Prof. Dr. Liers)
Cauerstraße 11
91058 Erlangen
- Phone number: +49 9131 85-67151
- Fax number: +49 9131 85-67162
- Email: frauke.liers@fau.de
- Website: https://www.datascience.nat.fau.eu/research/groups/ouda/members/frauke-liers/
Publications
- Adelhütte, D., Braun, K., Liers, F., & Tschuppik, S. (2024). Minimizing delays of patient transports with incomplete information: A modeling approach based on the Vehicle Routing Problem. Or Spectrum. https://doi.org/10.1007/s00291-024-00788-6
- Aigner, K.-M., Goerigk, M., Hartisch, M., Liers, F., & Miehlich, A. (2024). A Framework for Data-driven Explainability in Mathematical Optimization. In Proceedings of the The 38th Annual AAAI Conference on Artificial Intelligence. Vancouver, CA.
- Bernhard, D., Liers, F., & Stingl, M. (2024). A Gradient-Based Method for Joint Chance-Constrained Optimization with Continuous Distributions. (Unpublished, Submitted).
- Bernhard, D., Liers, F., & Stingl, M. (2024). Robust chance-constrained optimization with discrete distributions. (Unpublished, Submitted).
- Dienstbier, J., Liers, F., & Rolfes, J. (2024). A Safe Approximation Based on Mixed-Integer Optimization for Non-Convex Distributional Robustness Governed by Univariate Indicator Functions. (Unpublished, Submitted).
- Glomb, L., Liers-Bergmann, F., & Rösel, F. (2024). Fleet & tail assignment under uncertainty. Discrete Optimization, 52. https://doi.org/10.1016/j.disopt.2024.100836
- Hoch, B., Liers-Bergmann, F., Neumann, S., & Zaragoza Martínez, F.J. (2024). The non-stop disjoint trajectories problem. Discrete Optimization, 52. https://doi.org/10.1016/j.disopt.2024.100837
- Kreuz, S., Apeleo Zubiri, B., Englisch, S., Buwen, M., Kang, S.G., Ramachandramoorthy, R.,... Rolfes, J. (2024). Improving reconstructions in nanotomography for homogeneous materials via mathematical optimization. Nanoscale Advances. https://doi.org/10.1039/d3na01089a
- Kreuz, S., Apeleo-Zubiri, B., Englisch, S., Kang, S.-G., Ramachandramoorthy, R., Spiecker, E.,... Rolfes, J. (2024). Improving reconstructions in nanotomography for homogeneous materials via mathematical optimization. (Unpublished, Submitted).
- Kuchlbauer, M., Dienstbier, J., Muneer, A., Hedges, H., Stingl, M., Liers, F., & Pflug, L. (2024). Quality Control in Particle Precipitation via Robust Optimization. Computers & Chemical Engineering. https://doi.org/10.1016/j.compchemeng.2024.108619
- Lüer, L., Peters, I.M., Smith, A.-S., Dorschky, E., Eskofier, B., Liers-Bergmann, F.,... Brabec, C. (2024). A digital twin to overcome long-time challenges in photovoltaics. Joule, 8, 1-17. https://doi.org/10.1016/j.joule.2023.12.010
- Wagner, F., Egger, D., & Liers, F. (2024). Optimized Noise Suppression for Quantum Circuits. (Unpublished, In review).
- Aigner, K.-M., Burlacu, R., Liers, F., & Martin, A. (2023). Solving AC Optimal Power Flow with Discrete Decisions to Global Optimality. Informs Journal on Computing. https://doi.org/10.1287/ijoc.2023.1270
- Aigner, K.-M., Bärmann, A., Braun, K., Liers, F., Pokutta, S., Schneider, O.,... Tschuppik, S. (2023). Data-driven Distributionally Robust Optimization over Time. INFORMS Journal on Optimization. https://doi.org/10.1287/ijoo.2023.0091
- Frank, U., Dienstbier, J., Tischer, F., Wawra, S., Gromotka, L., Walter, J.,... Peukert, W. (2023). Multidimensional Fractionation of Particles. Separations, 10(4). https://doi.org/10.3390/separations10040252
- Glomb, L., Liers, F., & Rösel, F. (2023). A stochastic optimization approach for optimal Tail Assignment with knowledge-based predictive maintenance. CEAS Aeronautical Journal. https://doi.org/10.1007/s13272-023-00663-0
- Glomb, L., Liers, F., & Rösel, F. (2023). Optimizing integrated aircraft assignment and turnaround handling. European Journal of Operational Research, 310(3), 1051 - 1071. https://doi.org/10.1016/j.ejor.2023.03.036
- Gutina, D., Bärmann, A., Roeder, G., Schellenberger, M., & Liers-Bergmann, F. (2023). Optimization over decision trees: a case study for the design of stable direct-current electricity networks. Optimization and Engineering. https://doi.org/10.1007/s11081-023-09788-x
- Wagner, F., Bärmann, A., Liers, F., & Weissenbäck, M. (2023). Improving Quantum Computation by Optimized Qubit Routing. Journal of Optimization Theory and Applications. https://doi.org/10.1007/s10957-023-02229-w
- Aigner, K.-M., Clarner, J.-P., Liers, F., & Martin, A. (2022). Robust Approximation of Chance Constrained DC Optimal Power Flow under Decision-Dependent Uncertainty. European Journal of Operational Research. https://doi.org/10.1016/j.ejor.2021.10.051
- Aigner, K.-M., Schaumann, P., von Loeper, F., Martin, A., Schmidt, V., & Liers, F. (2022). Robust DC Optimal Power Flow with Modeling of Solar Power Supply Uncertainty via R-Vine Copulas. Optimization and Engineering. https://doi.org/10.1007/s11081-022-09761-0
- Anjos, M., Hante, F.M., & Liers-Bergmann, F. (2022). Special issue on Energy Networks. Mathematical Methods of Operations Research. https://doi.org/10.1007/s00186-022-00791-z
- Biefel, C., Liers, F., Rolfes, J., Schewe, L., & Zöttl, G. (2022). Robust Market Equilibria under Uncertain Cost. European Journal of Operational Research, 302(3), 1230-1241. https://doi.org/10.1016/j.ejor.2022.02.030
- Biefel, C., Liers, F., Rolfes, J., & Schmidt, M. (2022). Affinely Adjustable Robust Linear Complementarity Problems. SIAM Journal on Optimization, 32(1), 152-172. https://doi.org/10.1137/20M1359778
- Hoch, B., & Liers, F. (2022). An integrated rolling horizon and adaptive-refinement approach for disjoint trajectories optimization. Optimization and Engineering. https://doi.org/10.1007/s11081-022-09719-2
- Hoch, B., & Liers, F. (2022). An Integrated Rolling Horizon and Adaptive-Refinement Approach for Disjoint Trajectories Optimization. Optimization and Engineering. https://doi.org/10.1007/s11081-022-09719-2
- Kreimeier, T., Kuchlbauer, M., Liers, F., Stingl, M., & Walther, A. (2022). Towards the Solution of Robust Gas Network Optimization Problems Using the Constrained Active Signature Method. In Proceedings of the 10th International Network Optimization Con- ference (pp. 45 - 50). Aachen, Germany.
- Kuchlbauer, M., Liers, F., & Stingl, M. (2022). Adaptive bundle methods for nonlinear robust optimization. Informs Journal on Computing, 34(4), 2106 - 2124. https://doi.org/10.1287/ijoc.2021.1122
- Kuchlbauer, M., Liers, F., & Stingl, M. (2022). Outer approximation for mixed-integer nonlinear robust optimization. Journal of Optimization Theory and Applications, 195, 1056–1086. https://doi.org/10.1007/s10957-022-02114-y
- Leithäuser, N., Adelhütte, D., Braun, K., Büsing, C., Comis, M., Gersing, T.,... Wrede, S. (2022). Decision-Support Systems for Ambulatory Care, including Pandemic Requirements: Using Mathematically Optimized Solutions. BMC Medical Informatics and Decision Making. https://doi.org/10.1186/s12911-022-01866-x
- Adelhütte, D., & Liers, F. (2021). Γ–counterparts for robust nonlinear combinatorial and discrete optimization.
- Antunovic, A., Amiri, E., Biefel, C., Steinbock, G., Aulin, J., Liers, F., & Gerstacker, W. (2021). Dynamic Sectorization in Multi-Panel Massive MIMO Systems. In Proceedings of the 2021 IEEE 4th 5G World Forum.
- Dienstbier, J., Aigner, K.-M., Rolfes, J., Peukert, W., Segets, D., Pflug, L., & Liers, F. (2021). Robust Optimization in Nanoparticle Technology: A Proof of Principle by Quantum Dot Growth in a Residence Time Reactor. Computers & Chemical Engineering. https://doi.org/10.1016/j.compchemeng.2021.107618
- Glomb, L., Hoch, B., Liers, F., & Rösel, F. (2021). Network planning and routing problems over time: Models, complexity and algorithms. In Petra Mutzel, Rasmus Pagh, Grzegorz Herman (Eds.), Leibniz International Proceedings in Informatics, LIPIcs. Lisbon, PT: Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing.
- Glomb, L., Liers, F., & Rösel, F. (2021). A rolling-horizon approach for multi-period optimization. European Journal of Operational Research, unbekannt(unbekannt). https://doi.org/10.1016/j.ejor.2021.07.043
- Liers, F., Martin, A., Merkert, M., Mertens, N., & Michaels, D. (2021). Solving mixed-integer nonlinear optimization problems using simultaneous convexification: a case study for gas networks. Journal of Global Optimization. https://doi.org/10.1007/s10898-020-00974-0
- Liers, F., Schewe, L., & Thürauf, J. (2021). Radius of Robust Feasibility for Mixed-Integer Problems. Informs Journal on Computing. https://doi.org/10.1287/ijoc.2020.1030
- Roeder, G., Ott, L., Maier, A., Wunder, B., Wienzek, P., Bärmann, A.,... Schellenberger, M. (2021). Analysis and Improvement of LVDC-Grid Stability using Circuit Simulation and Machine Learning - A Case Study. In Proceedings of the NEIS 2021 Conference on Sustainable Energy Supply and Energy Storage Systems. Hamburg.
- Adelhütte, D., Aßmann, D., Gonzàlez Grandòn, T., Gugat, M., Heitsch, H., Liers, F.,... Wintergerst, D. (2020). Joint model of probabilistic/robust (probust) constraints with application to gas network optimization. Vietnam Journal of Mathematics. https://doi.org/10.1007/s10013-020-00434-y
- Ambrosius, M., Grimm, V., Kleinert, T., Liers, F., Schmidt, M., & Zöttl, G. (2020). Endogenous Price Zones and Investment Incentives in Electricity Markets: An Application of Multilevel Optimization with Graph Partitioning. Energy Economics. https://doi.org/10.1016/j.eneco.2020.104879
- Dienstbier, J., Schmölder, J., Burlacu, R., Liers, F., & Kaspereit, M. (2020). Global optimization of batch and steady-state recycling chromatography based on the equilibrium model. Computers & Chemical Engineering, 135, 106687. https://doi.org/10.1016/j.compchemeng.2019.106687
- Hupp, L., Kapolke, M., Liers, F., Martin, A., & Weismantel, R. (2020). Mixed-Integer Reformulations of Resource-Constrained Two-Stage Assignment Problems.
- Liers, F., Martin, A., Merkert, M., Mertens, N., & Michaels, D. (2020). Towards the Solution of Mixed-Integer Nonlinear Optimization Problems using Simultaneous Convexification.
News and Recent Accomplishments:
- Backs the Women in Datascience Conference‘s Student Organizing Committee
Exploring Digital Twin Applications in Accelerating PV Material Research
On sunny days, up to 60% of the electricity in Germany is produced by photovoltaics (PV). This is good news…A Digital Twin to Overcome Long-time Challenges in Photovoltaics
Lüer L., Peters I.M., Smith A.S., Dorschky E., Eskofier B., Liers-Bergmann F., Franke J., Sjarov M., Brossog M., Guldi D.M.,…FAU Solar members in the DFG review board
Four members of FAU Solar have been elected to the DFG review board for the next year! We warmly congratulate…Video on Teaming-up across Disciplines @FAU Solar: A Dive into Photovoltaic Data Analysis
This video highlights the fusion of technology and data insights shaping renewable energy’s future. By leveraging data analytics, the researchers…A Positive Semidefinite Safe Approximation of Multivariate Distributionally Robust Constraints Determined by Simple Functions
Jana Dienstbier, Frauke Liers, Jan Rolfes https://arxiv.org/abs/2310.05612 Single-level reformulations of (non-convex) distributionally robust optimization (DRO) problems are often intractable, as…A Safe Approximation Based on Mixed-Integer Optimization for Non-Convex Distributional Robustness Governed by Univariate Indicator Functions
Jana Dienstbier, Frauke Liers, Jan Rolfes https://arxiv.org/abs/2301.11185 In this work, we present algorithmically tractable safe approximations of distributionally robust optimization…Women in Optimization (09. – 12. April 2024)
We are pleased to announce the fifth installment of the “Women in Optimization” workshop series supported by SFB Transregio 154.…A Digital Twin to overcome long-time challenges in Photovoltaics
Larry Lüer, Marius Peters, Ana Sunčana Smith, Eva Dorschky, Bjoern M. Eskofier, Frauke Liers, Jörg Franke, Martin Sjarov, Mathias Brossog,…