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传统配送方案无法明确物流配送各个环节细节工作，配送路径与理想路径不一致，存在配送时间过长、配送效率较低的问题，为此，提出基于改进遗传算法的应急物资配送路径优化方法。在充分考虑驾驶员心理状态情况下，计算2个受灾点之间的距离。在描述应急物资配送路径问题后，构建应急物资配送路径模型，并设置一个物资配送时间窗，计算违反配送原则的惩罚成本，优化物流配送细节工作内容。采用自然数编码、解码方式，获取独立子路径。采用节约算法构造问题初始解，设计种群初始化过程。通过顺序交叉操作方式，获取子代个体。通过变异操作、局部搜索操作分析2个受灾点之间相关性。待达到最大进化迭代次数后，输出问题最优解，即应急物资配送优化路径。由实验结果可知，所提方法路径优化结果与理想结果一致，所花费的时间最短，能够为应急救援工作提供一定的技术支持。

The traditional distribution scheme cannot clarify the details of each link of logistics distribution, the distribution path is inconsistent with the ideal path, and the distribution time is too long, resulting in lower distribution efficiency. A scheme of optimization of the emergency supplies distribution path based on improved genetic algorithm is proposed. After fully considering the driver's psychological state, this paper calculates the distance between the two disaster points. After describing the emergency supplies distribution path problem, this paper builds the emergency supplies distribution path model, sets up a supplies distribution time window, calculates the penalty cost for violating the distribution principle, and optimizes the details of logistics distribution. Natural number encoding and decoding are used to obtain the independent sub paths. The saving algorithm is used to construct the initial solution of the problem and design the population initialization process. Through sequential crossover operation, the offspring individuals are obtained. The correlation between the two disaster points is analyzed by mutation operation and local search operation. After reaching the maximum number of evolutionary iteration, the optimal solution of the problem is output, i.e., the optimal path of emergency supplies distribution. The experimental results show that the path optimization results of the proposed method are consistent with the ideal results, and the time spent is the shortest, which can provide some technical support for emergency rescue work.