Vehicle Routing ProblemOptimization

Optimize delivery routes for multiple vehicles with capacity constraints, time windows, and real-world logistics challenges

Multi-vehicle routing
Time windows
Cost optimization

The Challenge

Vehicle Routing Problems are among the most complex optimization challenges in logistics. You need to find the most efficient routes for multiple vehicles while respecting:

  • Vehicle capacity constraints
  • Customer time windows
  • Driver working hours
  • Traffic and distance optimization
  • Fuel costs and vehicle maintenance

Typical Problem Size

~500
Customer nodes
~30
Vehicles
Data format: routes.csv with coordinates, demands, time windows, and vehicle capacities

How QuantFenix Optimizes VRP

Our multi-objective routing automatically selects the best backend for your specific problem size and constraints

Classic Baseline

Starts with proven OR-Tools algorithms for immediate results

Fast, reliable solutions using classical optimization methods. Perfect for smaller instances or when you need quick results.

Hybrid Quantum

Quantum-inspired algorithms for complex, large-scale problems

When problem size grows or constraints become complex, we automatically route to quantum backends for better solutions.

Budget-Capped

Hard budget limits prevent cost overruns

Set maximum compute budgets per run. We'll find the best solution within your cost constraints.

Expected Results

Indicative ranges based on real customer implementations

Cost Reduction

≥20%

Targets set in pilot; typical ranges shown in benchmarks

Runtime Improvement

−25–50%

Faster decision-making compared to manual/legacy runs

What You Get

• Optimized route assignments for all vehicles
• Detailed cost breakdown and savings analysis
• Complete audit trail with reproducible results
• PDF report ready for management review

Ready to optimize your routes?

Upload your routes.csv and get instant cost analysis with optimized vehicle assignments