  In practice, e.g. in delivery and service scenarios, Vehicle-Routing-Problems
(VRPs) often imply repeated decision making on dynamic customer requests. As in
classical VRPs, tours have to be planned short while the number of serviced
customers has to be maximized at the same time resulting in a multi-objective
problem. Beyond that, however, dynamic requests lead to the need for
re-planning of not yet realized tour parts, while already realized tour parts
are irreversible. In this paper we study this type of bi-objective dynamic VRP
including sequential decision making and concurrent realization of decisions.
We adopt a recently proposed Dynamic Evolutionary Multi-Objective Algorithm
(DEMOA) for a related VRP problem and extend it to the more realistic (here
considered) scenario of multiple vehicles. We empirically show that our DEMOA
is competitive with a multi-vehicle offline and clairvoyant variant of the
proposed DEMOA as well as with the dynamic single-vehicle approach proposed
earlier.
