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A deterministic linear optimization model for allocating schools to zones

Author

Listed:
  • I Gac

    (University of Chile)

  • F Martínez

    (University of Chile)

  • A Weintraub

    (University of Chile)

Abstract

This paper presents a deterministic linear optimization model to support decisions on optimal allocation of schools to zones, its characterization and assignment of students, maximizing the social benefits of school owners and students. Students are assumed to show a multi-attribute behaviour, considering as important not only location, as is usual in the literature, but also quality of education and infrastructure, school costs and other attributes. There is heterogeneity of supply and demand. Students are classified by place of residence and socio-economic characteristics. Schools can be private, subsidized or free municipal ones. The model developed is applied to data of one of the municipalities of Santiago. The results obtained under different scenarios tend to confirm the expected demand's behaviour. This model could be used to guide decisions of both school owners or municipalities as well as students towards an equilibrium closer to a social optimum.

Suggested Citation

  • I Gac & F Martínez & A Weintraub, 2009. "A deterministic linear optimization model for allocating schools to zones," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(7), pages 895-905, July.
    • Handle: RePEc:pal:jorsoc:v:60:y:2009:i:7:d:10.1057_palgrave.jors.2602630
    DOI: 10.1057/palgrave.jors.2602630
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    References listed on IDEAS

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    2. Cohen, Ernesto & Martínez, Rodrigo & Donoso S., Pedro & Aguirre, Freddy, 2003. "Localización de infraestructura educativa para localidades urbanas de la Provincia de Buenos Aires," Políticas Sociales 6064, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
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    Cited by:

    1. Jesica de Armas & Helena Ramalhinho & Marta Reynal-Querol, 2022. "Improving the accessibility to public schools in urban areas of developing countries through a location model and an analytical framework," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-27, January.
    2. Mayerle, Sérgio F. & Rodrigues, Hidelbrando F. & Neiva de Figueiredo, João & De Genaro Chiroli, Daiane M., 2022. "Optimal student/school/class/teacher/classroom matching to support efficient public school system resource allocation," Socio-Economic Planning Sciences, Elsevier, vol. 83(C).

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