基于改进麻雀搜索算法的疏散路径规划

建筑物内部发生火灾时环境复杂多变，传统疏散指示路径难以根据实际火场情况进行有效的路径规划，为此引入一种改进麻雀搜索算法。首先，根据实际火源位置设置麻雀算法预警值参数，实现算法路径规划过程中对于火源等危险区域的躲避。其次，对麻雀搜索算法位置更新公式进行优化，引入精英反向学习策略以及带有动态权重系数的正弦余弦优化算法，进一步针对麻雀搜索算法易于陷入局部最优解的问题进行改进。最后，采用栅格法搭建3种地图类型，将改进麻雀搜索算法与基本麻雀搜索算法、灰狼算法进行路径规划对比，得出该改进麻雀搜索算法在火灾复杂环境下有较好的危险区域躲避能力以及路径规划能力，在路径长度、拐点个数方面优于另外两种对比算法，在搜寻时间方面稍有不足。

Evacuation path planning based on improved sparrow search algorithm

The environment is complex and changeable when a fire breaks out inside a building, so it is difficult for the traditional evacuation route to make effective route planning according to the actual fire situation. In this paper, an improved sparrow search algorithm is introduced. Firstly, the early warning value parameters of sparrow algorithm are set according to the actual fire location, so as to avoid dangerous areas such as fire sources in the process of path planning. Secondly, the location updating formula of sparrow search algorithm is optimized, and elite reverse learning strategy and sine and cosine optimization algorithm with dynamic weight coefficient are introduced to further improve the problem that sparrow search algorithm is easy to fall into local optimal solution. Finally, the grid method is used to build three types of maps. By comparing the improved sparrow search algorithm with the basic sparrow search algorithm and Grey Wolf algorithm in path planning, it is concluded that the improved sparrow search algorithm has better ability to avoid dangerous areas and path planning in complex fire environment, and is superior to the other two comparison algorithms in path length and number of inflection points, but has a slight deficiency in search time.