The primary focus of this project was to collaborate with the client's team to formulate and implement a CVRP solution using Python that meets specific constraints and requirements of the company.

Other responsibilities included:

Utilize optimization libraries such as PyVRP to develop an efficient algorithm.

Optimize the algorithm for computational efficiency and scalability.

Perform testing and validation to confirm the accuracy of the solution.

One month to deliver the project

Problem Description:

Customers: 250 customers with varying demands, distributed theoretically according to a normal distribution N(8,3).

Customer Locations: Customer locations are distributed theoretically according to a normal distribution N(2,1).

Vehicles: Up to 50 vehicles are available, each with a maximum capacity of 40 boxes.

Routing Constraints: Vehicles do not return to the depot and service only one route each.

Assignment: Each customer is assigned to a single vehicle.

Customer Limit: Each vehicle can serve a maximum of 7 customers.

Demand: Each customer has a minimum demand of 3 boxes.