In many logistics operations, efficiency is not just about the number of stops but about the distinct locations visited. To optimize routes effectively, you may want to limit the number of unique pickup or drop-off clusters a vehicle visits in a sequence, rather than just the total number of stops.
In some logistics scenarios, it's necessary to limit the number of trips a vehicle can make from a depot. For example, a driver might have a maximum number of routes they can perform in a shift, or a vehicle might need to return to the depot for reloading or maintenance after a certain number of tours.
In the context of the Stateless API, Vehicle Efficiency refers to a set of constraints designed to optimize and control how a vehicle's capacity is utilized throughout its route. These constraints allow you to enforce rules about minimum loads during a trip and maximum loads at the end of a trip.
A node's servicetime says how long the stop takes. Sometimes that depends on the vehicle as well as the stop: a large truck needs longer to park and open up than a van, and a vehicle without a tail lift is slower to unload. **Vehicle service time** adds a vehicle-dependent amount on top of each node's own servicetime whenever that vehicle serves the node.
In the context of a Vehicle Routing Problem (VRP), slack (also commonly called waiting time) is the unproductive idle time that a vehicle and driver must spend at a stop.
While a system-wide depot generally represents a centralized hub where vehicles load or park, Vehicle Start and End Locations are specialized vehicle constraints that define explicitly where a specific vehicle begins and finishes its shift.
Defining the start time and end time for a vehicle is crucial for accurately modeling real-world logistics operations. These parameters define the working shift of a driver or the availability window of a vehicle.