PROGRESS IN GEOGRAPHY ›› 2016, Vol. 35 ›› Issue (11): 1352-1359.doi: 10.18306/dlkxjz.2016.11.005

• Orginal Article • Previous Articles     Next Articles

Optimizing school distribution with constraints of school size after school consolidation in rural China: A case study of Yanqing District, Beijing City

Teqi DAI1(), Liang WANG1, Yuchao ZHANG2, Cong LIAO1   

  1. 1. School of Geography, Beijing Normal University, Beijing 100875, China
    2. Beijing Education Examinations Authority, Beijing 100083, China
  • Online:2016-11-25 Published:2016-11-25
  • Supported by:
    Fundamental Research Funds for the Central Universities, No.2015KJJCB30


With urbanization and the decrease of rural population, a large number of rural schools in China has been merged. How to optimize the layout of schools has become a research hotspot. In 2008, China issued the standards of school size, but the impact of the standards on the layout of schools is yet to be researched. In this study, based on existing location allocation models, constraints of the size of schools were applied to build a model of school layout optimization, which also considered the constraint of maximum distance to school. We chose the primary schools in Yanqing District, Beijing for case study and used the branch and bound algorithm and global optimal solution method to solve the model. The data range from 1995 to 2010, which include 295 primary schools distributed in nearly all villages at the start, and 46 primary schools after the large-scale school merging. The results show that after the school size constraints were applied in the optimization model, 65.22% of the rural schools need to be relocated, which reflects the significant impact of school size constraints. But school spatial distribution pattern remained essentially unchanged at the town and township scale, with the proximity index higher than 1, larger than before. After applying the size constraints, the distribution pattern of schools was still a discrete type. But the degree of dispersion has decreased. The optimal solution with school size constraints can satisfy the national standards. At the same time, the optimal solution results in an increase of schooling distance at 135 m per student, which is acceptable. Finally, this study examined the implications of the results for the school layout optimization policy.

Key words: rural school, school consolidation, school size, school layout optimization, P-median model, Yanqing District, Beijing City