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Optimization & Decision Systems
Simulation, Optimization & Planning
Shifts, resources, constraints. A problem that grows exponentially. We solve it.
Planning team shifts is not a simple problem. It is a combinatorial problem: every variable added — a legal constraint, a preference, an absence — exponentially multiplies the number of possible combinations. Doing it manually means hours of work, errors, conflicts and suboptimal solutions. Doing it well, at scale, is beyond human capability.
We build automatic optimization systems that handle complex constraints, respect rules and people, and produce optimal operational plans in times a human could never achieve.
Problems we solve
Blocked knowledge, critical dependencies and inefficiencies holding back growth
Slow and inefficient manual planning
Building a shift plan takes hours, sometimes days. And often the result is not even optimal.
Legal constraints that are difficult to manage
Collective agreements, labor regulations, maximum hours, mandatory rest periods: every rule is a constraint the planner must keep in mind.
Individual preferences ignored
Workers have different needs. Ignoring them costs in terms of satisfaction, turnover and productivity.
Impossible scalability
As the team and constraints grow, problem complexity increases exponentially. Manual planning does not scale.
Costly errors
An uncovered shift in a critical department, a violated constraint, insufficient coverage.
Use Cases
Real projects, measurable results
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Hospitals and healthcare facilities manage large teams, 24/7 shifts, strict regulations, and indivi…
Healthcare sector — Automatic shift generation
Hospitals and healthcare facilities manage large teams, 24/7 shifts, strict regulations, and individual worker preferences. We developed an optimization system that automatically generates shifts taking into account all legal and contractual constraints, individual operator preferences, and the coverage needed for each department.
A problem of exponential complexity, solved automatically and repeatably.
Technology Corner
The architecture and technologies that make the difference
Our projects don't rely on off-the-shelf solutions. Every system is designed on the right architecture for the specific problem — and the technology choice makes the difference between a tool that works in demo and one that holds up in production.
Constraint Optimization
- ✓ Google OR-Tools CP-SATcore solver for complex combinatorial problems
- ✓ Hybrid approachconstraint programming, integer linear programming, SAT solving
- ✓ Conflict-Driven Clause Learning (CDCL)efficient navigation of enormous solution spaces
- ✓ Hard and soft constraintsmodeling legal constraints and individual preferences with priority management
- ✓ Multi-objective optimizationcoverage, fairness, preferences and compliance simultaneously
Interested in this service?
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