The parking cruising problem can be attributed to the unbalanced spatial parking space occupancy in the parking lot with multiple trip purposes and high traffic volumes, and it has already become an obstacle to improving travel efficiency. This study aims to investigate the reasons for the unbalanced occupancy of parking spaces and develop strategies to achieve spatial equilibrium by reducing parking cruising time. A field survey is first conducted to analyze the factors influencing parking space choice behavior, such as searching distances, walking distances, parking price, and parkers’ attributes. Based on the survey, a mixed logit model is calibrated to reveal parking space choice patterns of different parkers. Afterwards, the parking lot is divided into three zones based on searching distances and walking distances, using the K-means algorithm. According to the results, a simulation-based optimization model is then established, for minimizing the variance of average occupancy. An optimal pricing strategy is obtained at last. A case study in Nanjing, China, is conducted to verify the feasibility and rationality of the proposed method. The difference between weekdays and weekends is explored. The results show that, with the optimal strategies, the standard deviation of average occupancy in each zone decreases by 39.52% during weekends and 42.29% during weekdays. Finally, political implications and recommendations on the layout design of facilities and the adoption of differential parking pricing strategies are provided.