The work aims to minimize the route cost and maximize the customer satisfaction under limited resources by considering the carbon emissions generated during service nodes and vehicle transportation as well as the customer satisfaction on the basis of the traditional cold chain logistics vehicle routing problem model. A multi-objective low-carbon cold chain logistics vehicle routing problem model was constructed, and the local search idea of mountain climbing algorithm was applied to the sparrow search algorithm to form an improved sparrow search algorithm. Then, the improved algorithm was used to solve the cold chain logistics distribution path optimization problem in a certain area of Shanghai. The results were compared with the results of the other two intelligent optimization algorithms before the improvement:the improved sparrow search algorithm had faster optimization speed and better optimization ability, and the improved algorithm had higher efficiency on carbon emission of the model. Based on the national low-carbon policy, a low-carbon cold chain logistics transport model that is in line with the current situation is designed, and the transport scheme is solved by improving the optimization algorithm, which verifies the effectiveness of the local search idea of the mountain climbing algorithm on the sparrow search algorithm and the rationality of the low-carbon cold chain logistics vehicle routing model constructed.