Daniel Schermer, M. Sc.
Daniel Schermer studied Business Management and Engineering in the field of Electrical Engineering at the University of Kaiserslautern. He received his Bachelor's and Master's deegrees in 2016 and 2018, respectively.
In addition to his positions as undergraduate and graduate assistant, he gained practical experiences as an intern at the Robert Bosch GmbH in Homburg (Germany) and the Middle East Internet Group in Dubai (United Arab Emirates).
As of April, 2018 Daniel Schermer works as a research fellow at the chair of Business Information Systems & Operations Research.
His main research interests include: artificial intelligence, combinatorial optimization, and high performance computing.
Building 42 , Room 416
Telephone: +49 631 205 2936
(from Monday to Friday)
by appointment only
- A branch‐and‐cut approach and alternative formulations for the traveling salesman problem with drone.
Networks, Vol. 76, Nr. 2, (2020)
- A hybrid VNS/Tabu search algorithm for solving the vehicle routing problem with drones and en route operations.
Computers & Operations Research, Vol. 109, (2019)
- A matheuristic for the vehicle routing problem with drones and its variants.
Transportation Research Part C: Emerging Technologies, Vol. 106, (2019)
- The Drone-Assisted Traveling Salesman Problem with Robot Stations.
Proceedings of the 53rd Hawaii International Conference on System Sciences, (2020)
- Integration of Drones in Last-Mile Delivery: The Vehicle Routing Problem with Drones.
Operations Research Proceedings 2018, (2019)
- The Traveling Salesman Drone Station Location Problem.
Optimization of Complex Systems: Theory, Models, Algorithms and Applications, Vol. 991, (2019)
- Algorithms for Solving the Vehicle Routing Problem with Drones.
Intelligent Information and Database Systems, Vol. 10751, (2018)
- A Hybrid Evolutionary Approach for Solving the Traveling Thief Problem.
Computational Science and Its Applications – ICCSA 2017, Vol. 10405, (2017)
- Swarm of agents for guarding an Art Gallery: A computational study.
2016 IEEE Symposium Series on Computational Intelligence (SSCI), (12/2016)