One-Day Travel Planning Using a Genetic Algorithm

Travel planning is a critical aspect of tourism, presenting significant challenges for visitors exploring unfamiliar cities. The Tourist Trip Design Problem (TTDP) focuses on optimizing routes for tourists interested in visiting multiple Points of Interest (POIs) to enhance the efficiency of daily sightseeing activities in a city. Our study models the TTDP using the Orienteering Problem (OP) while considering user-specific travel constraints such as time limitations and fixed start and end points at particular POIs. Additionally, an innovative approach is introduced that incorporates user interest levels based on personalized visit duration preferences into the travel planning model. By utilizing genetic algorithms, this approach ensures robust search efficiency and facilitates both global and local optimizations. Empirical evaluations on real-world datasets demonstrate that our proposed algorithm outperforms in achieving diverse and optimized travel plans and is confirmed to be effective in scalability concerning different problem sizes and optimization goals.