Ravelijn

dr. D. Guericke MSc (Daniela)

Assistant Professor
BMS-HBE-IEBIS
Ravelijn 3355
d.guericke@utwente.nl
+31534899791
Business card

Daniela Guericke is Assistant Professor for Stochastic Operations Research at the Section Industrial Engineering and Business Information Systems. Her research focuses on sustainable operations by utilizing (stochastic) operations research and optimization methods in application areas such as energy systems and health care. In particular, she is interested in decision-making under uncertainty and solving large-scale optimization problems.

Daniela received her PhD in Business Information Systems from the Decision Support and Operations Research Lab, Paderborn University. Afterwards,  she worked as a postdoctoral researcher at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). In 2020, she became Assistant Professor for Decision-making under Uncertainty in Integrated Energy Systems at DTU. In 2021, Daniela received the Young Researchers Award of the German OR Society (GOR e.V.).

Expertise

  • Computer Science

    • Models
    • Control

  • Engineering

    • District Heating System
    • Energy Engineering
    • Optimization
    • Energy Systems
    • Networks
    • Planning

Organisations

Publications

2025

An Optimization Framework for Managing Resource Flows in Hubs for Circularity (2025)Circular Economy and Sustainability, 5(5), 3909-3938. Article 135414. Wang, J., Trivella, A., Guericke, D. & Yazan, D. M.https://doi.org/10.1007/s43615-025-00592-6Designing an optimized fueling infrastructure for a hydrogen railway system (2025)Journal of Rail Transport Planning and Management, 35. Article 100524. Trivella, A., Balha, A. & Guericke, D.https://doi.org/10.1016/j.jrtpm.2025.100524A two-level approach for multi-objective flexible job shop scheduling and energy procurement (2025)Cleaner Energy Systems, 10. Article 100178. Burmeister, S. C., Guericke, D. & Schryen, G.https://doi.org/10.1016/j.cles.2025.100178

2024

A memetic NSGA-II for the multi-objective flexible job shop scheduling problem with real-time energy tariffs (2024)Flexible services and manufacturing journal, 36, 1530-1570. Burmeister, S. C., Guericke, D. & Schryen, G.https://doi.org/10.1007/s10696-023-09517-7Correction: A memetic NSGA‑II for the multi‑objective flexible job shop scheduling problem with real‑time energy tariffs (2024)Flexible services and manufacturing journal, 36, 1571-1573. Burmeister, S. C., Guericke, D. & Schryen, G.https://doi.org/10.1007/s10696-023-09530-wA Stochastic Investment Planning Model for On-Site Energy Sector Coupling in Data Centers (2024)[Working paper › Preprint]. Social Science Research Network (SSRN). Guericke, D., Dominković, D. F. & Junker, R. G.https://doi.org/10.2139/ssrn.5005870A generic stochastic network-based formulation for production optimization of district heating systems (2024)Energy Systems (E-pub ahead of print/First online). Guericke, D., Schledorn, A. & Madsen, H.https://doi.org/10.1007/s12667-024-00698-0Frigg 2.0: Integrating price-based demand response into large-scale energy system analysis (2024)Applied energy, 364. Article 122960. Schledorn, A., Charousset-Brignol, S., Junker, R. G., Guericke, D., Madsen, H. & Dominković, D. F.https://doi.org/10.1016/j.apenergy.2024.122960

2023

Frigg 2.0: Integrating Price-Based Demand Response into Large-Scale Energy System Analysis (2023)[Working paper › Preprint]. Social Science Research Network (SSRN). Schledorn, A., Charousset-Brignol, S., Junker, R. G., Guericke, D., Madsen, H. & Dominković, D. F.https://doi.org/10.2139/ssrn.4617554Can occupant behaviors affect urban energy planning? Distributed stochastic optimization for energy communities (2023)Applied energy, 348. Article 121589. Leprince, J., Schledorn, A., Guericke, D., Dominkovic, D. F., Madsen, H. & Zeiler, W.https://doi.org/10.1016/j.apenergy.2023.121589

Research profiles

Current projects

IS2H4C - From Industrial Symbiosis to Hubs for Circularity

Sustainable Circular Economy Transition: From Industrial Symbiosis to Hubs for Circularity (IS2H4C) is a project funded by the Horizon Europe Programme of the European Union. IS2H4C project focuses on deploying systemic industrial symbiosis through innovative technologies like carbon capture and electrolysis. The initiative is driven by the vision of resource efficiency, renewable energy production, waste prevention, and fostering industrial-urban-rural symbiosis.

The project aims to develop the most innovative sustainable technologies and infrastructure integration in four demo hubs and is supported by ground-breaking research on societal, governmental, and business innovation for H4C. IS2H4C scales up industrial areas to H4C via  implementing systemic change and integrating the surrounding ecosystems to industrial areas.

Daniela Guericke is co-lead of the work package Modelling & optimisation for H4C development.

CARE-FLOW - Intelligent data-driven tools for cross-border collaboration in healthcare

The project’s objective is to develop and evaluate healthcare software products and algorithms that improve the streamlining of patient flows and capacities in the program area, ensuring access to and efficiency of healthcare. We focus on emergency services, hospitals, and care facilities and their collaboration across the border. Due to the geographical proximity in the border region, the duplication of, e.g., ambulances and (intensive care) beds is not absolutely necessary. Rather, the joint use of capacities across the border offers the opportunity to provide patients with the care they need and to reduce overcapacity. This is a complex planning task that requires a substantial amount of coordination. We support this planning task. We use methods from the fields of IT, artificial intelligence, and analytics to ultimately manage patient flows between healthcare facilities and capacities within the region intelligently using software and algorithms. The algorithms enable data-driven decisions based on demand forecasts. Besides regular demand, we also consider peak demand, e.g., pandemics, as cross-border collaboration is even more important due to the high demand. We develop the software based on feedback from our partners in the healthcare sector in order to remove barriers for practical  implementation. 

Scan the QR code or
Download vCard