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An Interactive Procedure for the School Boundary Problem with Declining Enrollment

Author

Listed:
  • Charles A. Holloway

    (Stanford University, Stanford, California)

  • Donald A. Wehrung

    (Stanford University, Stanford, California)

  • Michael P. Zeitlin

    (Stanford University, Stanford, California)

  • Rosser T. Nelson

    (University of California, Los Angeles, California)

Abstract

School districts in some urban areas are facing reduced enrollments. Educational and economic considerations dictate closing schools. Parents, on the other hand, often resist closing neighborhood elementary schools and object to having children periodically reassigned. This paper presents an interactive procedure for establishing, under conditions of declining enrollment, boundaries that reflect educational, economic, and parental concerns. The procedure can incorporate a variety of administrative policies and requires inputs from administrators regarding characteristics of the district. The multi-period planning horizon is decomposed by year with coordination taking place through the use of restriction in a linear programming problem that forms the basis for reassignment of districts. The emphasis is not on optimization but rather on the achievement of a solution which satisfies the objectives of each group. Feasibility checks are designed to reduce the number of alternatives that must be considered in detail, and feasible solutions can be compared on the basis of summary statistics.

Suggested Citation

  • Charles A. Holloway & Donald A. Wehrung & Michael P. Zeitlin & Rosser T. Nelson, 1975. "An Interactive Procedure for the School Boundary Problem with Declining Enrollment," Operations Research, INFORMS, vol. 23(2), pages 191-206, April.
    • Handle: RePEc:inm:oropre:v:23:y:1975:i:2:p:191-206
    DOI: 10.1287/opre.23.2.191
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    Cited by:

    1. Johnes, Jill, 2015. "Operational Research in education," European Journal of Operational Research, Elsevier, vol. 243(3), pages 683-696.
    2. Sven Müller & Knut Haase & Sascha Kless, 2009. "A Multiperiod School Location Planning Approach with Free School Choice," Environment and Planning A, , vol. 41(12), pages 2929-2945, December.
    3. Bruno, Giuseppe & Esposito, Emilio & Genovese, Andrea & Piccolo, Carmela, 2016. "Institutions and facility mergers in the Italian education system: Models and case studies," Socio-Economic Planning Sciences, Elsevier, vol. 53(C), pages 23-32.
    4. Takeshi Shirabe, 2009. "Districting Modeling with Exact Contiguity Constraints," Environment and Planning B, , vol. 36(6), pages 1053-1066, December.
    5. Carey, Malachy & Srinivasan, Ashok & Strauss, Robert P., 1996. "Optimal consolidation of municipalities: An analysis of alternative designs," Socio-Economic Planning Sciences, Elsevier, vol. 30(2), pages 103-119, June.
    6. F Caro & T Shirabe & M Guignard & A Weintraub, 2004. "School redistricting: embedding GIS tools with integer programming," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(8), pages 836-849, August.
    7. 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).
    8. C M S Sutcliffe & J L G Board, 1986. "Designing Secondary School Catchment Areas Using Goal Programming," Environment and Planning A, , vol. 18(5), pages 661-675, May.

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