Research on Application of Improved Genetic Algorithm in Urban Full Independent Tourist Route Planning

With the development of full independent tourist, people´s demand for humanization and rationalization in travel route planning is increasing. This paper addresses the problem of time-dependent tour planning in urban areas that may be of importance for people who like full independent tourist. The problem is determination of chronological sequences of attractions, restaurants and hotels or initial point during a specific period via several tools of transportation. This paper proposed a city full independent tourist route planning model on the basis of the traveling salesman problem´s model with time constraints, and constructed a genetic algorithm to solve the model. Ultimately achieve the prototypes of the full independent tourist route planning system. The experimental results show that the expected feasibility and practicability of the proposed model have been achieved, and the proposed adapted algorithm can find an optimum itinerary according to introduce constraints.