Abstract: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, then proposes a two-stage algorithm to solve the proposed model. Firstly, k-means clustering algorithm was used to determine the location of distribution centers, and then a time-space two-factor customer division method was proposed to determine the customers served by the chosen distribution center. Finally, particle swarm algorithm was used to optimize the vehicle routings of each distribution center.Two numerical examples show 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.