Location-routing is an important problem in supply chain management and logistic systems. This paper studies the location-routing problem with time windows with the consideration of the distribution centers capacitate constraints. It establishes a multi-objective programming model to minimize the total cost and maximize the customer satisfaction, and proposes a two-stage algorithm to solve the proposed model. Firstly, the k-means clustering algorithm is used to determine the location of distribution centers, and then a time-space two-factor customer division method is proposed to determine the customers served by the chosen distribution center. Finally, the particle swarm algorithm is used to optimize the vehicle routings of each distribution center. Numerical examples illustrate that the proposed algorithm can effectively reduce the total cost of logistics operation and the total distribution routing length compared with other existing algorithms, providing a new solution to the location-routing problem with capacitate constraint and time windows.