In order to cope with the real-time solution requirements of the Vehicle Routing Problem with Time Window (VRPTW) in the era of big data, this study proposed an improved parallel ant colony algorithm based on Spark platform. At the algorithm level, the improved state transition rule and roulette selection mechanism are used to construct the initial solution, and the k-opt local search is used to optimize the path construction. In addition, the improved pheromone update strategy of max-min ant colony algorithm is applied. At the implement level, the ant colony is encapsulated into RDD, which is operated by Spark API to realize distributed construction solution. The experimental results of the Solomon benchmark and Gehring & Homberger benchmark show that the proposed algorithm can improve the accuracy and speed of large-scale problems.