Abstract: Aiming at the problem that it is difficult to evacuate from large public buildings when a fire occurs, a fire evacuation path planning method based on improved Harris Hawks optimization algorithm was proposed. Firstly, the digital map required for path planning was modeled by the grid method, and the objective function of path planning evaluation was constructed with the shortest path as the goal. Secondly, Latin hypercube sampling, lens inverse learning strategy and adaptive weighting factor were introduced to improve the traditional Harris Hawks optimization algorithm, and B-spline curve smoothing method was used to smooth the planning path. Finally, it was compared with the other three algorithms in the case of no fire and fire to verify the excellent performance of the proposed algorithm. The experimental results show that in the case of no fire, the average path length of the proposed algorithm is 21.82 m, and the planning time is 20.4 s, which are reduced by 5.9% and 6.8% respectively compared with those before improvement. In the case of fire, the average path length is 22.45 m, and the planning time is 21.5 s, which is 39.0% and 48.8% lower than that before the improvement. Compared with other comparison algorithms, the proposed algorithm has good advantages in path search speed, average length and stability, and can obtain the comprehensive optimal path planning performance.

Key words: path planning, Harris Hawks optimization algorithm, fire, fire evacuation, grid method