By Marlin Wolf Ulmer
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Additional info for Approximate Dynamic Programming for Dynamic Vehicle Routing
4 Constraints As main constraints, we differentiate between customers’ time windows, drivers’ working hours, and vehicles’ capacities. , a violation may not be allowed. , violations are allowed but result in penalties or costs respectively. 1 Time Windows In many cases, customers have to attend home to receive the service or delivery. Therefore, time windows are communicated. A time window for a customer is defined by the earliest and latest possible point of time the customer can be visited by a vehicle.
The service time may depend on the time for searching a parking space, or, on the requirements of the customer. This may be especially the case for technicians and maintenance workers. Another field of uncertain service times is healthcare. In many cases, the physicians are unaware of the patient’s condition before they arrive. As a result, the required amount of time to spend at the patient’s home significantly differs. 3 Demands In some cases, the volume of customer demands are large and the vehicles’ loading capacities have to be considered in planning.
Chapter 3 Rich Vehicle Routing: Applications In Chap. 2, we have described the environment, vehicle routing is conducted in. In the following, we present the practical fields of routing applications inducing RVRPs. We analyze the applications regarding uncertainty and requirement for planning. We focus on routing in urban environments. The main purpose of this section is to give an overview of the important entities and underlying components in RVRPs as well as the most common objectives, constraints, and main drivers of uncertainty based on the findings of Sect.
Approximate Dynamic Programming for Dynamic Vehicle Routing by Marlin Wolf Ulmer