Transport Planning Optimization

Making transport planning more effective by improving resource utilisation and reducing unnecessary trips.

Arbor-IA Logistics

Problem

Traditional transport planning generates waste every day: underutilised vehicles, ineffi cient routes, and avoidable mileage. The result is higher costs and poorly optimised operations.

Solution

An optimisation algorithm analyses shipments, identifi es the best possible combinations, and supports planners in their day-to-day decisions, cutting unnecessary journeys and empty runs.

Benefits

Lower transport operating costs

Fewer kilometres and fewer trips translate into direct cost savings, with a measurable impact on the bottom line.

Better utilisation of fleet and available resources

Vehicles are used to their full capacity, reducing redundancy and optimising the allocation of containers and tractor units.

Greater reliability and control over plannin

The system supports planners in daily decision-making, reducing reliance on manual judgement and increasing service predictability.

Scalability and adaptability

The model is designed to grow and adapt easily to more complex networks, higher volumes, and new operational constraintswithout requiring a complete redesign.