Christoph Kerscher, M.Sc.
Contact
Room: 1563
Tel: +49 (0)89 289 28203
Fax: +49 (0)89 289 28210
christoph.kerscher@tum.de
Office Hours
by appointment
Research interests
- Methods:
- Optimization under uncertainty
- Machine Learning
- Topics:
- Future Mobility
-
Data-Driven Optimization in Operations Management
Current teaching (Winter 2022 / 2023)
Academic Career and Positions held to date
- Since 10/2021: Research assistant at the Chair of Logistics and Supply Chain Management (Prof. Dr. Stefan Minner), Technical University of Munich
Academic Services
- Since 2021: Reviewer for International Journal of Production Economics
Academic Education
- 2018: Graduation as Master of Science in Industrial Engineering (M.Sc.) at University of Duisburg-Essen
- 2016: Term abroad at Nanyang Technological University, Singapore
- 2015 – 2018: Studies of Industrial Engineering at University of Duisburg-Essen
- 2015: Graduation as Bachelor of Science in Industrial Engineering (B.Sc.) at University of Magdeburg
- 2011 – 2015: Undergraduate studies of Industrial Engineering at University of Magdeburg
Professional Experience
- 2020 – 2021: Senior Analyst Strategic Fleet Management at Sixt SE, Munich
- 2018 – 2019: Consultant Data and Analytics at Ernst & Young GmbH, Munich
Master Theses:
-
Evaluation Strategies for Clustering Approaches in the Context of Vehicle Routing Problems
-
Decomposition Methods for Large-Scale VRPTW
-
Decomposition Strategies for Vehicle Routing Problems with a Heterogenous Fleet
-
Solving vehicle routing problems with pickup and deliveries subject to loading and unloading constraints
- Using machine learning methods to reduce large vehicle routing problems
Bachelor Theses:
-
Real-time vehicle routing: Problem, methods, data, and evaluation
-
Knowledge graphs in logistics networks: applications and use cases for supply chain innovation
- The stochastic traveling salesman problem with temporally and spatially correlated travel times: Models, methods and applications
Project Studies:
- Delivery route re-optimization using real-time data on mobile device (in cooperation SAP Labs Munich)
Interdisciplinary Projects for Informatics (IDP)