A Multiperiod School Location Planning Approach with Free School Choice

Abstract

SummaryThe subject of this contribution is a new approach for multi-period school location planning in urban areas. Most of the existing approaches in the field do not consider free school choice nor they are able to consider substitution effects between school locations. We minimize the location and transport costs with respect to students choosing the school with the highest utility. Since these school choice probabilities (determined by a mixed multinomial logit model) depend on the available schools, we have to consider two steps: First, we generate for each period a set of scenarios indicating which school is open and which is not. For each scenario we allocate the students to available schools according to capacity and utility. Second, we select for each period one scenario in order to minimize total costs. Problems with long time planning horizon and a large number of demand points are solvable. We apply this approach to schools of the City of Dresden, Germany.

Parental preferences in the choice for a specialty school

“…In the future, this model has the potential to predict the demand for new schools, offering new or existing theme specialties. This kind of spatial predictive analytics has been shown to be effective for analyzing the school network configuration in cities such as Dresden in Germany (Müller, Haase, & Kless, 2009). …”

Exposing Unobserved Spatial Similarity: Evidence from German School Choice Data

“…The literature about school choice modeling usually focuses on racial mix, tuition fees, and travel-to-school distance (see section "School Choice Modeling"). Because free school choice is seldom found in many countries, most school location planning approaches do not account for spatial substitution (Müller 2008;Müller, Haase, and Kless 2009), but some references lead one to believe that spatial substitution patterns between school locations exist (Manski and Wise 1983;Borgers et al 1999;Müller 2009).…”

Bildungsstandorte und demographischer Wandel

“…Mit hilfe eines nicht-linearen entscheidungsmodells werden die Schüler für jede mögliche Kombination von perioden und Szenarien auf geöffnete Schulen verteilt, so dass die Abweichung von den empirisch ermittelten Schulwahlwahrscheinlichkeiten und die Kapazitätsüber-schreitung minimiert werden. eine Kapazitätsüberschreitung liegt dann vor, wenn in einer periode mehr Schüler an einer (Müller et al 2009). im dritten Schritt dieses optimierungsansatzes wird dann in jeder periode ein Szenario ausgewählt, so dass die gesamtkosten inklusive der Kosten, die durch Öffnung oder Schließung von Standorten entstehen, über den planungszeitraum minimiert werden (vgl.…”