A logistics company struggles with planning efficient routes for its fleet, leading to high travel distances, fuel consumption, and delays. The problem is exacerbated by variables such as traffic conditions, delivery time windows, vehicle capacity, and delivery priorities. Manual planning is inefficient and often results in higher operational costs and customer dissatisfaction.
Features
- Simulates and generates optimized route plans.
- Analyse and learns from historical data to improve route.
- Offers real-time data.
- Optimization Algorithms for efficient route planning.
Solution:
The solution can systematically determine the most efficient routes for the fleet, reducing overall travel distance, fuel use, and time while meeting delivery requirements. The system can handle various complexities in route planning, such as multiple vehicles, delivery constraints, and dynamic conditions.