Scheduling & Mobility
Optimised vehicle, circulation and shift plans for transport.
Mathematical optimisation | Anexia Digital Engineering
Complex rules become optimal plans.
Dispatching, routing and resource planning are mathematical problems. We solve them with exact methods and smart heuristics, provably close to the optimum. Your vehicles, teams and budgets work where they create the most value.
Optimisation with substance.
Many planning tools guess. We calculate. Operations research combines exact mathematics with learning methods, so decisions stay transparent, robust and economical.
Exact methods
MILP, constraint programming and graph algorithms deliver solutions with a quality guarantee.
Heuristics at scale
Metaheuristics and decomposition scale where exact models reach their limits.
AI in real time
Reinforcement learning decides on disruptions in seconds, not hours.
Provably near optimal
We quantify the quality of every solution, often within one per cent of the optimum.
The right method for the task.
MILP
Mixed-integer linear programming models hard constraints and finds the provably best solution.
Constraint Programming
Declarative modelling of complex rules, ideal for duty and shift logic.
Graphs & network flow
Shortest paths, flows and assignments, solved efficiently with Dijkstra, A* and flow algorithms.
Metaheuristiken
Genetic algorithms, simulated annealing and tabu search for very large instances.
Decomposition
Column generation and Benders break large problems into solvable parts.
Reinforcement Learning
Learning agents make real-time decisions and improve with every run.
We calculate. Bring us your planning problem.
Whether vehicle circulation, duty roster or network: we model your task and deliver provably good solutions. Talk to our engineers.
