<p>In planning tourism routes, the currently used planning methods cannot plan the optimal routes. Aiming at this problem, the study introduces revenue iteration combined with the improved interest distribution matrix to construct a tourism planning model based on the interest distribution matrix to plan the optimal tourism route. The tourism user interest model is built through the interest distribution matrix, which can effectively collect user interest and preference information and provide various personalized services to users with different requirements. The study adopts the value of the revenue iteration function in revenue iteration to deal with the factors affecting the user’s sense of experience. The tourism planning model proposed in the study was compared with two models commonly used for planning tourism routes. Compared to the other two models, the model's mean absolute error value was substantially lower, at just 0.786. Furthermore, the model's mean absolute percentage error consistently stayed below 0.60, suggesting it performed noticeably better than the other two models. Additionally, the tourism planning model indicated in the study was able to plan the best travel routes for various interest preferences, regardless of whether the user requested a destination or not, when compared to morphological spatial pattern analysis and minimum cumulative resistance model. The outcomes reveal that the model can plan the optimal routes that are most suitable for tourism users when planning tourism routes. This model could be implemented in intelligent tourism systems to provide customized, efficient travel planning for diverse user groups.</p>