With over 79 million people forcibly displaced, forced human migration becomes a common issue in the modern world and a serious challenge for the global community. The Flee is a validated agent-based social simulation framework for forecasting the population displacements in the armed conflict settings. In this paper, we present two schemes to parallelize Flee, analyze computational complexity of those schemes, and outline results for benchmarks of our parallel codes with the real-world and synthetic scenarios on four state-of-the-art systems including a new European pre-exascale system, Hawk. On all testbeds, we evidenced high scalability of our codes. It exceeds more than 16,384 cores in our largest benchmark with 100 million agents on Hawk. Parallelization schemes discussed in this work, can be extrapolated to a wide range of ABSS applications with frequent agent movement and lesser impact of direct communications between agents.