In the multi-source and multi-point environment, the path optimization involving dynamic loading and product distribution in dynamic logistics is a very complicated problem. Aiming at the diversification of goods demand in the actual distribution process and the path optimization problem of multi-vehicle delivery and high idling rate, this study proposes a new scheduling and distribution method. By establishing a vehicle loading and distribution path model, using the multi-source point multi-destination, weight correction, path optimization, etc. as constraints, a new way of simulating cell division is used to generate the next generation and improved the existing genetic algorithm to solve the problem. This method optimizes the generation of the initial population can quickly obtain the global optimal solution, jump out of the genetic premature convergence, get the best path, reduce the distribution cost and improve the distribution efficiency.