Reasonable planning of tourist routes is crucial for enhancing tourist satisfaction. This paper addresses the problem of tourist route optimization by proposing a solution that considers multiple influencing factors. A tourist route optimization model is established with the objective of maximizing tourist satisfaction, taking into account constraints such as tourist preferences, travel time, budget, and attraction opening hours. To improve the algorithm, a heuristic information mechanism and an adaptive adjustment factor are introduced to the ant colony algorithm, enhancing its global search ability and convergence speed. Using Southwest China as a case study, the results show that the proposed approach increases tourist satisfaction by 18.28% and 11.83% compared to the minimum travel budget plan and the random plan, respectively. This study provides a more efficient and accurate solution for personalized tourist route planning.

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