  We consider a distribution logistics scenario where a shipping operator,
managing a limited amount of resources, receives a stream of collection
requests, issued by a set of customers along a booking time-horizon, that are
referred to a future operational period. The shipping operator must then decide
about accepting or rejecting each incoming request at the time it is issued,
accounting for revenues, but also considering resource consumptions. In this
context, the decision process is based on dynamically finding the best
trade-off between the immediate return of accepting the request and the
convenience of preserving capacity to possibly exploit more valuable future
requests. We give a dynamic formulation of the problem aimed at maximizing the
operator revenues, accounting also for the operational distribution costs. Due
to the "curse of dimensionality", the dynamic program cannot be solved
optimally. For this reason, we propose a mixed-integer linear programming
approximation, whose exact or approximate solutions provide the relevant
information to apply some commonplace revenue management policies in the
real-time decision-making. Adopting a capacitated vehicle routing problem as an
underlying distribution application, we analyze the computational behaviour of
the proposed techniques on a set of academic test problems.
