Paper Info
Title
REGAL - A Regionalization framework for school boundaries.
Abstract
Due to constant shifts in population and changing demographics, school boundary processes take place to make adjustments to school attendance zones. This spatial problem has multiple criteria like locations of schools, their capacity utilization, proximity, presence of geographical/ man-made barriers, etc. In this paper, we formulate the problem of designing school boundaries as a spatially-constrained clustering/ regionalization problem and propose an automated approach called REGAL for solving it. REGAL is two-stage framework that starts by creating a candidate solution with regard to domain constraints such as school locations and spatial contiguity. Then a local search method improves the quality of the candidate solution by optimizing population balance and compactness of school zones while satisfying problem constraints. Experimentally, we demonstrate the efficacy of the REGAL framework on actual datasets from two school districts in the US.
Year
DOI
Venue
2019
10.1145/3347146.3359377
SIGSPATIAL/GIS
Keywords
Field
DocType
constrained clustering, local search, optimization, spatial clustering
Data science,Computer science,Artificial intelligence,Machine learning
Conference
ISBN
Citations 
PageRank 
978-1-4503-6909-1
0
0.34
References 
Authors
1
7
Name
Order
Citations
PageRank
Subhodip Biswas129512.07
Fanglan Chen200.68
Zhiqian Chen3138.04
Andreea Sistrunk410.70
Nathan Self51019.65
Chang-Tien Lu61097115.77
Naren Ramakrishnan71913176.25