Bring order to complexity
From logistics to shift planning: we identify the best solution for highly complex scenarios. Meet every operational constraint and optimize your resources without compromise.
What are they?
Constraint-based problem solving deals with systems where solutions are not unconstrained but must adhere to strict—and often conflicting—conditions: operational limits, finite resources, organizational rules, timeframes, priorities, and dependencies.
In such contexts, the challenge is not simply to “find a solution,” but to identify the best possible solution within a highly constrained space.
The role of constraints
A constraint defines what cannot be violated. Ignoring it leads to theoretically valid solutions, but unusable in reality.
Recognizing and correctly modeling it, however, allows you to:
- drastically reduce the solution space
- make the problem formalizable
- transform complexity into structure
01
Modeling
The problem is translated into an abstract model: decision variables, explicit constraints and objective function.
02
Analysis of trade-offs
Not all constraints carry the same weight. Identifying the hard and fast ones and the negotiable ones is crucial.
03
Selection of tools
The best tools are selected to achieve the result, for example OptaPlanner
04
Optimization
We seek solutions that maximize overall effectiveness without violating the imposed conditions.
05
Operational validation
A solution is only valid if it works in the real context, not just in the model.
Our projects
Hospital transport
Hospital transport represents a concrete example of a problem with multiple constraints:
- Exam and therapy times
- Limited availability of operators and vehicles
- Non-negotiable clinical priorities
