In order to ensure timely and efficient delivery of emergency resources to disaster areas, the work aims to construct a multi-objective optimization model for the multi-objective emergency location routing problem by taking into account the time windows of the disaster area and road safety during resources transportation, with the objectives of minimizing economic costs, time penalty costs, and maximizing road safety. At the same time, an improved salp swarm algorithm is designed to solve the problem, in order to verify the feasibility of the model and the effectiveness of the algorithm. Based on the characteristics of the model, the algorithm was improved by combining random generation and greedy algorithm to generate initial solutions. The position update operation of the original algorithm was improved by crossover operators and neighborhood search operators. The elite retention strategy of NSGA-Ⅱ was introduced to improve the performance of the algorithm. After test of multiple examples, this algorithm could quickly obtain a cluster of Pareto solutions and was compared with the original salp swarm algorithm. The improved algorithm had better performance. For the emergency location routing problem of timely response after a disaster, the improved salp swarm algorithm has certain advantages, and can provide decision-makers with satisfactory solutions based on the preferences of multiple objectives. It has a certain reference value for the field of emergency location routing problems.