Currently, tourists seek to optimize their time when planning a trip to another country to visit attractions and places that match their tastes and preferences. Among these preferences is slow or relaxed tourism, which demands visiting less popular places and having in mind conscious relaxed tourism. Linear programming has been used in some studies to solve optimization problems related to tourist routes, but its use is limited due to the complexity of the constraints in these problems. In contrast, constraint programming can handle complex constraints more naturally, allowing for better constraint modeling and more efficient problem solving. This paper addresses this problem by using constraint programming techniques for the optimization of tourist routes. Constraint programming has been proven to be an effective technique for solving optimization problems related to tourist routes given its ability to model complex constraints and conflicts in solutions naturally. The results obtained in this article demonstrate that constraint programming using complete search techniques provides better results compared to linear programming. In particular, the proposed technique achieved the optimal solution for 70% of the tested instances, surpassing the results obtained by state-of-the-art studies and highlighting its efficiency in execution time. In summary, it is concluded that constraint programming is a more effective and efficient technique than linear programming in optimizing tourist routes in view of its ability to naturally model complex constraints and conflicts in solutions.