Self-optimizing systems for better decisions
We work to ensure efficient and flexible logistics processes
Fluctuating order volumes, limited resources, volatile markets, and heterogeneous data sources are making logistics and production processes increasingly complex. At the same time, companies must quickly and reliably align production schedules, inventory levels, batch sizes, routes, and shifts with available resources and their capacities.
We develop self-optimizing systems that translate data into robust recommendations for action through mathematical optimization, simulation, and machine learning. We work with you to make operations more efficient, ensure decisions are made with greater transparency, and adapt processes flexibly to new conditions. From analysis and model development to implementation, we guide you on your journey toward data-driven and future-proof decision support.
Let’s talk about your logistics challenges.
Solutions for your logistics needs
This is how we can support you
Unlock new potential in logistics with tailored technologies based on operations research methods.
Optimizing processes
- Make logistics and production processes more efficient through mathematical optimization and simulation
Planning resources dynamically
- Manage inventory, buffers, capacity, delivery routes, and other planning parameters based on demand
Taking risk into account
- Ensure sound decision-making even when demand fluctuates or data is incomplete or unreliable
Responding automatically to changes
- Continuously adapt planning models to current data and new conditions
Comparing scenarios
- Transparently assess the impacts of different decisions and develop well-founded courses of action
Improving robustness
- Identify bottlenecks and disruptions early on and devise appropriate countermeasures more quickly
Together to the next level
How you can collaborate with us
We apply the latest scientific and technological methods specifically to logistics and production, and support our clients and partners through the systematic design, development, and application of quantitative methods.
Analysis
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From the collection and analysis of data relevant to decision-making ...
Decision
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via decision modeling and automated decision-making ...
Integration
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all the way to the context-aware integration of acquired information into business systems.
How you benefit
- Shorter planning times
- More efficient use of resources
- Clearer decisions
- Stronger processes
Logistics
Reference projects
Here are a few selected reference projects in logistics.




