Application in Emergency Vehicle Routing Choosing of Particle Swarm Optimization Based Ant Colony Algorithm

With the speeding up of urbanization in our country, the situation of urban emergency is getting more and more serious; therefore, it is necessary to promote the study in urban emergency management, so as to enhance the city ability of resisting the emergency. Based on the defects of the emergency vehicle routing choosing, the paper puts forward a particle swarm optimization based ant colony algorithm. The algorithm uses particle swarm algorithm to optimize the important parameter of ant colony system, making the parameters of the ant colony system unnecessary to be obtained by artificial experience or cut-and-trial method, but adaptively select by particle searching, which optimizes the defects of long searching time and easily to be premature or stagnation of the basic ant colony algorithm. Algorithm simulation results show that the particle swarm optimization based ant colony algorithm is good in searching for the optimal solution, and which has a short search time, a good convergence performance, and which is not easily into the local optimum, its performance is better than the basic ant colony algorithm.