  In this paper, we deal with a size-variable group of pedestrians moving in a
unknown confined environment and searching for an exit. Pedestrian dynamics are
simulated by means of a recently introduced microscopic (agent-based) model,
characterized by an exploration phase and an egress phase. First, we study the
model to reveal the role of its main parameters and its qualitative properties.
Second, we tackle a robust optimization problem by means of the Particle Swarm
Optimization method, aiming at reducing the time-to-target by adding in the
walking area multiple obstacles optimally placed and shaped. Robustness is
sought against the number of people in the group, which is an uncertain
quantity described by a random variable with given probability density
distribution.
