The thesis is about the collaborative optimization of multi-depot vehicle routing problem with split pickup and cross-dock door assignment, considering joint distribution of multiple cross-dock center, split pickup and cross-docking operation, establish an optimization model which is aimed at minimizing the sum of vehicle dispatching cost, vehicle fuel cost, fixed and transportation cost of forklift in cross-dock center and time window penalty cost. According to the characteristics of the problem, the hybrid genetic algorithm is designed through adding the directed optimization method of the particle swarm algorithm, evolutionary reversal and elitist retention strategy are also used to improve the solution quality. The validity of the model and algorithm is verified by multiple examples, the influence of distribution mode and vehicle type on the distribution scheme formulation are also analyzed. The results show that the optimization scheme obtained by the model in this thesis can effectively reduce the distribution cost. The research results expand and enrich the research of vehicle routing problem with cross-docking, and provide theoretical basis for logistics enterprises to formulate the decision distribution scheme scientifically.