In order to improve the replenishment scheme of a cigarette factory supplier and realize the intelligent logistics, the work aims to propose a distance optimization model based on immune algorithm by comprehensively considering the process characteristics of the production supply line and the replenishment demand feedback signal to improve the intelligent logistics and the replenishment efficiency. By analyzing and sequencing the customer's demand orders, the existing problem was transformed into traveling salesman problem through modeling. Then, the immune algorithm was used to solve the problem, and the simulation was carried out on Matlab. The results showed that the two curves of the average fitness value and the optimal fitness value converged closely. At the same time, the order sequence was optimally arranged to improve the efficiency of intelligent logistics. The distance optimization model based on immune algorithm is effective and can be used to improve the replenishment scheme of cigarette factory suppliers. At the same time, the order demand sequencing can be optimized and the intelligent logistics can be realized. Therefore, this scheme has positive significance for improving the operational efficiency of suppliers and meeting customer's demand.