Using genetic algorithm to optimize obstacle location in a crowded system

The basic social force model was modified to build a pedestrian dynamic model.Real-coded genetic algorithm with self-adaptive cross-over and mutation strategy was used to optimize obstacle setting.High performance computation platform was used to simulate and find the best setting of obstacles.Obstacle size,number and position in the crowd system containing pedestrians and rooms were optimized to improve pedestrian escape speed in a panic situation.These results have practical meaning for architectural design.