  In this paper, we focus on the modification of policies that can lead to
movement patterns and directional guidance of occupants, which are represented
as agents in a 3D simulation engine. We demonstrate an optimization method that
improves a spatial distancing metric by modifying the navigation graph by
introducing a measure of spatial distancing of agents as a function of agent
density (i.e., occupancy). Our optimization framework utilizes such metrics as
the target function, using a hybrid approach of combining genetic algorithm and
simulated annealing. We show that within our framework, the
simulation-optimization process can help to improve spatial distancing between
agents by optimizing the navigation policies for a given indoor environment.
