The School District Reorganization by Combining with Traffic Congestion Data

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 their residence. With the support of the data provided by Baidu Map 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.