Abstract: Enterprise's shuttle bus location and route optimization problems play an important role in increasing the logistics management efficiency and operation expenditure control. Traditional researches optimize location and route separately, thus causing danger to ignore the close connection between them. In this paper, we propose an information entropy-based improved fuzzy c-means semi-supervised clustering algorithm for bus location optimization and experiments are conducted to evaluate the reliability and effectiveness of it. Thereafter, a shuttle bus route selection model is introduced and an enhanced ant colony optimization (ACO) algorithm is designed to obtain the optimal results.