abstract = "This paper proposes a new evolutionary algorithm-based
methodology for optimal crowd evacuation planning. In
the proposed methodology, a heuristic-based evacuation
scheme is firstly introduced. The key idea is to divide
the region into a set of sub-regions and use a
heuristic rule to dynamically recommend an exit to
agents in each sub-region. Then, an evolutionary
framework based on the Cartesian Genetic Programming
algorithm and an agent-based crowd simulation model is
developed to search for the optimal heuristic rule. By
considering dynamic environment features to construct
the heuristic rule and using multiple scenarios for
training, the proposed methodology aims to find generic
and efficient heuristic rules that perform well on
different scenarios. The proposed methodology is
applied to guide people's evacuation behaviours in six
different scenarios. The simulation results demonstrate
that the heuristic rule offered by the proposed method
is effective to reduce the crowd evacuation time on
different scenarios.",