In route planning we are given a graph and
a source and destination node. We want determine a source-destination path with
minimum costs (this could be for example time). Very often it is laso of
interest to consider other criteria, i.e. we may have constraints on the total
distance travelled or on the fuel consumption, etc. This can be modeled as a
constrained shortest path problem and thus be solved using the CNOP package.
Digital Elevation Model (DEM) of a part of the Alps. The underlying graph is a
grid graph. We are looking for a source-destination path that minimizes the
total accumulated height difference while not exceeding a given length. The
minimum length path is brown, the minimum heightdifference path is yellow, and
the minimum heightdifference path with length constraint is green.
Road graph (part of US). Congestion areas are shown green. We are looking for a
source destination path that minimizes congestion while not exceeding a given
length.
gmx.de