  The article presents a framework for the resolution of rich vehicle routing
problems which are difficult to address with standard optimization techniques.
We use local search on the basis on variable neighborhood search for the
construction of the solutions, but embed the techniques in a flexible framework
that allows the consideration of complex side constraints of the problem such
as time windows, multiple depots, heterogeneous fleets, and, in particular,
multiple optimization criteria. In order to identify a compromise alternative
that meets the requirements of the decision maker, an interactive procedure is
integrated in the resolution of the problem, allowing the modification of the
preference information articulated by the decision maker. The framework is
prototypically implemented in a computer system. First results of test runs on
multiple depot vehicle routing problems with time windows are reported.
