A Dynamic Route Optimization System for Logistics & Supply Chain Organizations

Challenges

Inefficient Routing: Existing manual or static routing methods resulted in long travel times, excessive fuel consumption, and missed delivery windows. It requires vehicle routing optimization to drive operational efficiency.

A Large Geographic Network: Pickup and delivery points were distributed across vast areas, which makes planning the most efficient routes difficult.

Real-time Adjustments: The system needed to adjust routes in real-time based on traffic conditions, weather disruptions, and unexpected delays in pickups or deliveries.

Data Management: Managing large datasets for geographic locations, vehicle capacities, and traffic patterns posed challenges in backend storage and processing.

Approach

• The Dynamic Route Optimization system is designed using an algorithm based on the Capacitated Vehicle Routing Problem (CVRP). It minimizes travel distance, fuel consumption, and time.
• The system uses clustering techniques to group pickup and delivery points based on geographic proximity (latitudes and longitudes) for more efficient route planning.
• To ensure continuous optimization of routes, we integrated real-time tracking of traffic, road conditions, and delays in the solution.
• The backend infrastructure is built on MySQL to store and manage location data, shipment details, and real-time traffic information.
• Open Source Routing Machine (OSRM) calculates the most efficient routes by considering real-time variables. The solution continuously adapts to changes in real time and provides route optimization with reduced travel time and operational costs.

Result

83% Reduction in Route Length and Transit Times

66% Improvement in Operational Efficiency

74% Cost Reduction due to Fuel Savings

87% Increase in Customer Satisfaction