I will optimize your delivery routes and supply chain using python algorithms

Google Maps optimizes a route for one vehicle. I solve the Vehicle Routing Problem (VRP) for entire fleets, considering constraints like vehicle capacity, time windows, driver shifts, and fuel costs simultaneously. This requires advanced mathematical algorithms (Operations Research).

While results vary, algorithmic optimization typically reduces mileage and fuel costs by 10-20% compared to manual planning. For a logistics business, this investment often pays for itself within the first month.

I need a structured dataset (Excel/CSV) containing delivery addresses, vehicle types/capacities, and any specific constraints (e.g., "delivery only between 8 AM and 10 AM").

Optimization models are complex mathematical structures. Changing a core constraint (e.g., "add a second depot") often requires rebuilding the mathematical model, not just a quick edit. Therefore, we must agree on all constraints before I begin the calculation.