Abstract: In order to reasonably solve the problem of distribution centre location and freight distribution in low-carbon logistics and transportation network system, firstly, the uncertainty of freight supply and demand is described through fuzzy variables and normal distribution, the comprehensive fuel consumption model is used to quantify the carbon emission in the process of transportation and distribution, and the Con-centration Index of Cover is proposed to reflect the balance of physical location distribution of logistics and distribution centre, Then, a multi-objective low-carbon logistics distribution centre location optimization model under uncertain environment is constructed; Secondly, considering the shortcomings of NSGA-Ⅱ algorithm in solving this kind of problems, such as low accuracy and uneven distribution of Pareto front, chaotic tent map is used to improve the uniformity of initial solution distribution in solution space, immune selection operator is introduced to improve the search ability of the algorithm, and a non-dominated sorting immune algorithm is proposed.Finally, the effectiveness of the model and algorithm was verified through a virtual example.The research results indicate that the constructed model can provide reference for decision-makers to choose reasonable location schemes in different backgrounds, and the proposed algorithm performs better in solving such problems.