The Challenge
A major logistics provider in North America faced operational inefficiencies in route planning for its last-mile deliveries. Managing a vast network of trucks and delivery locations, the client needed to improve last-mile efficiency, reduce idle time, and optimize route planning to cut down on delivery costs and time.
Existing manual routing processes lacked flexibility and failed to factor in real-time traffic patterns, driver regulations, and delivery schedules. The need for a smart, adaptive routing system was evident.
The Solution
Evalueserve developed a route optimization engine combining Mixed Integer Linear Programming (MILP) with heuristics to ensure both precision and computational efficiency for large-scale route planning. The model minimized total transportation costs while ensuring all shipments were delivered within their required appointment windows.
Key solution features included:
- Optimal sequence of delivery stops for each truck in the city fleet
- Assignments of shipments and drivers to trucks
- A dynamic front-end tool allowing users to:
- View and switch between alternate routes
- Analyze time and distance metrics
- Visualize vehicle movement from hub to delivery locations
Insight into service times, trailer utilization, and route-specific costs
Business Impact
With Evalueserve’s routing optimization:
-
The client improved operating income by more than $1M per month
-
Idle times and route overlaps were minimized
-
Real-time routing tool empowered planners to make faster, smarter decisions
-
Enhanced visibility into city trucks, including their capacities, loads, and time estimations
Overview & Impact
A leading logistics provider in North America partnered with Evalueserve to optimize last-mile delivery routes. By replacing manual planning with an intelligent, real-time routing engine, the client cut costs and improved operational efficiency.
