Smart Travel Route Planning Considering Variable Neighborhood Ant Colony Algorithm

Given the lack of autonomy in travel route planning and the difficulty to meet the individual demand of tourists at present, a smart travel route planning algorithm based on variable neighborhood ant colony algorithm is proposed. Firstly, models for the set of attractions of interest and characteristic inflections are established. The variable neighborhood ant colony is determined and combined to design a smart travel route planning algorithm based on the shortest path planning so that tourists can perform the smart planning of the optimal travel route after selecting scenic spots autonomously or using the intelligent machine intelligent machine. The numerical example has demonstrated that the proposed algorithm can output the route with the shortest distance while complying with the general rules of the travel ferry process, meeting the individual demand of tourists, and allowing them to satisfy the optimal motive interest.