A simulation of tourists and vehicles scheduling in scenic and its decision-making strategy

Today, more and more people like to take kinds of vehicles to travel, there are so many tourists and vehicles at every scenic, as a result, how to effectively solve problems between ecological environment protection and tourist development, how to wisely handle abnormal events of the scenes, such as quick response for incidences, safety of tourists, people/vehicles evacuation and so on. In this paper, we propose a multi-agent visual platform, which is used to simulate, show, evaluate and solve the most probably encountered abnormal events of the scenes. Based on this platform, we put up a model of the vehicle scheduling problem (VSP) about abnormal events of the scenes, and the data mining and decision tree algorithms are made and replaced randomly for a better and better decision solution about how to dispatch the vehicles, people. Abnormal events of the scenes are divided into three different situations: full load, not full load or have a time window. Finally, we build a complete model to verification our solution based on the platform.