With the developing economy and consumption level, the market demand for agricultural products is getting bigger and bigger, and the requirements for the level of agricultural logistics and distribution are also getting higher and higher, which also brings great opportunities and challenges to China’s agricultural logistics and distribution. Swarm intelligence optimization algorithm includes ant colony genetic algorithm, so this paper is based on ant colony genetic algorithm for logistics distribution path optimization for application research. Agricultural products are perishable, and in the process of logistics distribution, the distributor has to meet the customer’s demand, but also to achieve the minimization of product distribution time and cost. This paper firstly constructs the distribution model through the basic constraints and objective functions of the model; then designs the vehicle path dynamic optimization algorithm and sets the initial population size so as to achieve the optimization of the distribution path; finally, by comparing and analysing the ant colony genetic algorithm and the improved ant colony genetic algorithm, the improved ant colony genetic algorithm is used to analyse different distribution modes.