My research studies operational decisions in logistics systems where people, robots, vehicles, vessels, drones, and shared resources depend on one another. The central problems are synchronized operations and resource-efficient online decisions.
Research structure
The map shows how each project combines research areas and operating environments. Select a project, decision area, or environment to examine the connections.
Methods and evaluation
I use mathematical optimization, tailored heuristics, approximate dynamic programming, reinforcement learning, and data-driven decision models. The choice of method follows the operational problem and the time available for a decision.
Computational experiments and simulation measure performance. Interactive visualization supports diagnosis: it helps reveal fleet behavior, failure modes, and differences between methods, which can then guide revisions to the model or algorithm.