Research Of Travel Itinerary Planning With Android Phones Based On Ant Colony Algorithm

Thanks to the development of economy, people have more time to enjoy their lives. Thus traveling during holidays has become far more popular. Therefore, a good plan is a prerequisite for memorable travels, and it could also reduce the time and the cost that the travel would have taken. By doing so can leave tourists a much better experience. This paper start with the travel route planning problem to build its model, and some common methods are analyzed. Then the ant colony algorithm is selected to solve the problem, and put forward the improved algorithm to overcome its shortcomings. Finally, a travel route planning system was implemented and the route planning results were displayed on the Baidu map. The major work is as follows:(1) Travel route planning problem is a kind of combination optimization problem that contains multiple constraints. Based on the classical traveling salesman problem modeling, and combine the time and cost demands that tourists are concerned when choose the route line, this paper proposed the question modeling include travel time, waiting time, opening time as well as travel cost constraints. Study the commonly used method for the tourist route planning, including the accurate solution method, heuristic algorithms and intelligent optimization algorithms.(2) The ant colony algorithm is selected to solve the travel route planning problem after some algorithms comparison. An improved ant colony algorithm is proposed to overcome the disadvantages:the heuristic function is redefined from the prospective of time and cost; the ants are tagged with time label and cost label to find the optimal tour; the open time constraints of the sceneries are joined to the state transition formula; dynamic adjust the state transition control parameter. The experimental results show that the proposed algorithm is feasible.(3) The improved algorithm is applied on the Android platform, and a travel route planning system was designed and implemented. The route results are displayed on the Baidu map, and the route planning function between two sceneries are also provided. Finally make the system test, and the results show that the function module of the system reached the expected target and the system can running stable.