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As urban travelers seek personalized and efficient travel planning solutions, the utilization of heuristic algorithms has gained significant attention. This study focuses on the optimization of travel itineraries by integrating destination ratings and flexibility into the algorithm. The objective is to enhance personalized travel experience by considering traveler preferences and efficient scheduling of destinations. The method involves utilizing a Genetic Algorithm (GA) framework and collecting destination ratings creating flexible scenarios, where the locations of the destinations can be changed. The outcomes demonstrate the effectiveness of the algorithm in generating optimized travel itineraries. The substitution of a destination, for example a cafe in the flexible scenario resulted in a significant reduction in total travel time by about 14.3%. This indicates the algorithm’s capability to optimize travel schedules by incorporating flexibility and considering destination ratings. The study’s implications include enhanced personalization, improved travel efficiency, and a more satisfying travel experience.