Optimizing The Spatial Assignment Of Schools To Reduce Both Inequality Of Educational Opportunity And Potential Opposition Rate Through Introducing Random Mechanism Into Proximity-Based System

A serious spatial inequality of educational opportunity was revealed worldwide, for wealthy families can access good schools by buying real estate with good school' enrollment quota. Although the existing studies had revealed that random-based school assignment can significantly improve equality of opportunity allocation, random mechanism was adopted only in few places. Two major resistances of introducing random mechanism exist: the possibility of increased commuting distance to schools and the effected relative beneficiaries. In order to make the random-based allocation more feasible, this study proposes a spatial optimization model to take these two factors into account into proximity-based school assignment system. The proposed multi-objective allocation model, with the constraint conditions of assigning students to 3 closest schools and school capacities, was developed in this study to minimize the spatial disparity of educational opportunity and the potential opposition rate of introducing random mechanism into proximity-based assignment system. The model will be solved by a heuristic algorithm and applied to a case study area of Shijingshan District, Beijing. The results showed that the proposed model could improve spatial equality of educational opportunity significantly, but along with a minor increase on commuting distance to schools. In addition, potential opponents of introducing random mechanism decrease as the weight of parameters related to opposition rate increases in the model, reducing nearly 10% in the best case. Therefore, the solutions provided by proposed model may encounter less resistance in a democratic voting system. However, the results also indicated that there would be some relative beneficiaries who may oppose introducing random mechanism into proximity-based school system even in the best case. This implies that, to achieve equal educational opportunity in the context of proximity-based school system, optimized allocation is needed along with a more even distribution of educational resources.