Start and complete stops within their time windows. For example to the pick-up is ready to be collected and delivered.

Match skill requirements for jobs to drivers with those skills.

Allow jobs to require or prefer specific drivers.

Assign jobs early in their time windows to avoid running out of time later.

Manage the driver's vehicle load and capacity type to make sure drivers always have enough capacity for their jobs.

Make sure stops are scheduled in the correct order and that stops in the same job are assigned to the same driver.

With too few resources for all the work, schedule as much (priority) work as possible.

Add SLAs to stops to make sure they are scheduled on time.

Assign specific drivers to jobs, allow or prohibit job pooling, and use tags to include additional information about jobs and drivers.

Apply breaks for drivers, including lunch breaks and appointments.

Honor drivers' working hours. Avoid unnecessary overtime.

Reduce the travel time and mileage per driver. This increases productivity and reduces CO2 emissions.

Respond to changes in the field and adjust the plan in real-time. Timefold supports adjusting the plan to several unexpected scenarios.

Quickly offer customers time windows when drivers could complete their jobs.

Dispatch drivers to efficiently transport clients between places such as doctor or specialist appointments, dialysis centers, mental health services, etc. while reducing miles driven, improving on-time performance, and ensuring passenger comfort.

Plan same-day and on-demand deliveries of small parcels, documents, and packages. Typical operations involve dynamically assigning pick-up and delivery jobs to a fleet of couriers. The model helps reduce driving time, improve on-time delivery performance, and maximize courier utilization while respecting strict service-level agreements (SLAs).