  In typical applications of facility location problems, the location of demand
is assumed to be an input to the problem. The demand may be fixed or dynamic,
but ultimately outside the optimizers control. In contrast, there are settings,
especially in humanitarian contexts, in which the optimizer decides where to
locate a demand node. In this work, we introduce an optimization framework for
joint facility and demand location. As examples of our general framework, we
extend the well-known k-median and k-center problems into joint facility and
demand location problems (JFDLP) and formulate them as integer programs. We
propose a local search heuristic based on network flow. We apply our heuristic
to a hurricane evacuation response case study. Our results demonstrate the
challenging nature of these simultaneous optimization problems, especially when
there are many potential locations. The local search heuristic is most
promising when the the number of potential locations is large, while the number
of facility and demand nodes to be located is small.
