To enhance the efficiency of emergency logistics during the process of major public health risk governance, an efficient emergency logistics collaboration mechanism was designed based on the analysis of the behavioral characteristics of government and logistics enterprise. An evolutionary game model between local government and logistics enterprise was established to investigate the evolutional laws and paths of local government's supervision and logistics enterprise's collaboration. Then, the feasibility and effectiveness of the proposed model were verified based on the numerical simulation. The results indicate that the emergency logistics collaboration mechanism in major public health risk governance significantly depends on local government's supervision compared with the collaboration mechanism of commercial logistics and it makes the collaboration level of logistics enterprise fluctuate between 0.25 and 0.9 repeatedly. After the establishment of a dynamic reward and punishment mechanism for local government, the obtained collaboration level of logistics enterprise stabilizes at 0.46 when the number of games reaches 30. It can be seen that this dynamic reward and punishment mechanism improves the stability of emergency logistics collaboration mechanism significantly.

In order to solve two-echelon location-routing problem of distribution network, particle swarm optimization with path relinking integrated into particle update process was proposed. Three path relinking search modules with regarding transfer station, path and edge as the object were put forward according to the attributes of the solution of two-echelon location-routing problem. At the same time, on the basis of the different combinations of these search modules, four kinds of path relinking strategy were put forward. The test results on different scale examples show that the particle swarm optimization can solve two-echelon location-routing problem effectively, the first path relinking strategy has higher efficiency. The second one has higher stability, the third one has no obvious performance in every aspect, and the fourth one has higher quality solution. Key words: two-echelon location - routing problem; particle swarm optimization; path relinking; distribution