The fleet service allow you to abstract vehicles or field technicians/sales staff that have to visit multiple locations to perform their daily duties. Each fleet member would have the following required fields:
- Name: to provide a descriptive label to the member
- Departure Time: to define the time of the day when the specific fleet member would go out to perform their duties
- Location: the origin point where the fleet member depart from (generally a depot)
By default, every fleet member would be routed to go back to their origin point once the orders assigned to them are fulfilled, but the behaviour can be defined by flagging the "Back to origin" field.
In order to pre-filter what a specific fleet member can do, a list of attribute can be included so that orders would be assigned to them accordingly. For example, for vehicle that can deliver frozen goods, we could apply the attribute frozen while for field technicians we could add their specific skills (e.g. plumber, electrician).
This information will be used in combination to the order's requirement, to assign specific orders only to vehicle/staff that can actually perform them.
You can use this configuration of the fleet member to override the limits that would be provided during the creation of the optimization task. By default, all fleet member, if not specified differently, would inherit the limits from the optimization task. In case you want to override this behavior for a specific fleet member, you can use the fleet limits configuration.
The information that could be provided are the following:
- Max Orders: define the maximum number of orders that can be assigned
- Max Distance: define the maximum distance that fleet member can covered for one assignment
- Max Time: define the maximum time (which includes driving time, service time and waiting time) for one assignment
- Max Capacity: define the maximum capacity (e.g. in KGs) - useful for vehicles
- Max Volume: define the maximum volume (e.g. in m3) - useful for vehicles
One or more limits can be applied in combination to obtain the expected outcome.