Papers

1

Total Citations

12

H-Index

1

About

Michael Bortz is a researcher at the forefront of quantum computing applications in industrial optimization, with a particular focus on bridging the gap between emerging quantum technologies and real-world logistics challenges. His most notable work centers on benchmarking quantum-hybrid and quantum-inspired computing frameworks against classical solvers for complex scheduling problems. In his widely discussed 2023 case study, Bortz and collaborators tackled a transport robot scheduling problem drawn from genuine industrial settings, rigorously comparing D-Wave's quantum-classical hybrid framework, Fujitsu's quantum-inspired digital annealer, and Gurobi's industry-standard classical optimizer. This work, already accumulating 12 citations shortly after publication, stands as a valuable reference for practitioners and researchers evaluating the practical readiness of quantum technologies. By grounding his investigations in authentic industrial scenarios rather than purely theoretical constructs, Bortz makes a compelling case for the relevance of quantum and quantum-inspired methods in manufacturing and logistics. His research is particularly valuable for students and engineers seeking honest, evidence-based assessments of where quantum computing currently stands relative to classical approaches in solving hard combinatorial optimization problems.

Research Focus

Key Achievements

1
H-Index
1
Papers
12
Total Citations
12
Avg Citations/Paper
🏆 Most Cited Paper
An optimization case study for solving a transport robot scheduling problem on quantum-hybrid and quantum-inspired hardware
12 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 7
🏛 Institutions: Fraunhofer Institute for Industrial Mathematics

Top Papers

  1. 1

Key Collaborators

Contact & Links

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