ML-based Route Optimization Model

About Client & Their Requirements

Our Client is a unicorn software company in Sweden and represents the world’s largest network of printers. The client provides customized print products in 33 countries and serves more than 5 billion customers. They recently got more than $240 million in funding from a renowned venture capitalist. Our clients have On demand Print and Optimal Print as their products and they always ensure that customers situated across the globe will receive their orders within 72 hours. To have a resilient business,ensuring timeliness and product excellence, they need highly skilled Data scientists, Data & ML engineers to build scalable ML models for optimal route selection to maximize efficiency in delivery.

In pursuit of delivering operational excellence

Our client’s objective is to find the best route for vehicles having a limited carrying capacity for the items that shall be delivered. Keeping in mind their needs our strong data engineering arsenals adopted industry best practices and structured problem-solving frameworks to deliver the best ML model

• Our team worked on the “Capacitated Vehicle Routing Problem”
• Using Python, Solver Pulp, and Graph theory our team estimated the weights of the packages, demand, vehicle requirement, moving distance & location of the customers
• Our experts leveraged the majestic powers of Google map API & Matplotlib libraries of Python to trace the location of the client’s customers on the Google map and visualized the results
• The tech experts also utilized the S3 bucket framework for data security & scalability