Using private cars by parents to pick up children from school is one of the causes of traffic congestion. The existing school district division method is still not reasonable to solve the problem of student enrollment in nearby schools to the irresidence. With the support of the data provided by BaiduMap API and Beijing Municipal Education Commission, this paper proposes a multi-target school district division method.This method is realized by using combinatorial optimization with the three constraints–school capacity, road length and time consumption. The k-nearest neighbor algorithm was used to preprocess the student data, and the compound genetic algorithm was used to find the optimal combination of school district re-planning. We used the data of Shijingshan District of Beijing for simulation and visualized the traffic network status before and after school district re-planning. The experimental results confirmed that this method can effectively reduce the time of driving and alleviate the road congestion during morning and evening rush hours, which has reference significance for the existing school district planning scheme. Matriculation School in Kumbakonam
In recent years, traffic congestion has become increasingly serious, and typical tidal mode of transportation is particularly prominent in urban traffic. This brings some troubles to people’s daily travel. There is no doubt that the increasing number of private cars is the main cause of traffic congestion.Therefore, some measures were taken in  to reduce traffic congestion, like limiting the number of trips through the license plate tail number. However, there are also hidden factors that can cause traffic congestion, such as the way of school district plan. In Beijing, the school that the children can choose mainly depends on where their parents live. In addition, due to the attention of children’s education and travel safety, parents pick up their children by private car at the time of upper and lower school . The centralized division by residential areas is easy to cause local traffic congestion.In , the congestion data of school working days and rest days were compared by using the two-stage least squares regression method, which showed that the traffic congestion index increased by 20% when children were transported to and from school by private cars. The work in established the relationship model between a middle school in Beijing and the surrounding traffic condition.