Aiming at the Multi-Depot Vehicle Routing Problem with Time Window (MDVRPTW), an Improved Adaptive Large Neighborhood Search algorithm (IALNS) was proposed. Firstly, a path segmentation algorithm was improved in the stage of constructing the initial solution. Then, in the optimization stage, the designed removal and repair heuristic operators were used to compete with each other to select the optimal operator, a scoring mechanism was introduced for the operators, and the heuristic operator was selected by roulette. At the same time, the iteration cycle was segmented and the operator weight information was dynamically adjusted in each cycle, effectively to prevent the algorithm from falling into local optimum. Finally, simulated annealing mechanism was adopted as the acceptance criterion of the solution. The relevant parameters of the IALNS were determined by experiments on the Cordeau normative instances, and the solution results of the proposed algorithm were compared with other representative research results in this field. The experimental results show that the solution error between IALNS and Variable Neighborhood Search (VNS) algorithm does not exceed 0.8%, even better in some cases; compared with the multi-phase improved shuffled frog leaping algorithm, the average time-consuming of the proposed algorithm is reduced by 12.8%, and the runtime is shorter for most instances. So the above results verify IALNS is an effective algorithm for solving MDVRPTW.