Application of the p-Median Problem in School Allocation


This paper focus on solving the problem of optimizing students’ orientation. After four years spent in secondary school, pupils take exams and are assigned to the high school. The main difficulty of Education Department Inspection (EDI) of Dakar lies in the allocation of pupils in the suburbs. In this paper we propose an allocation model using the p-median problem. The model takes into account the distance of the standards imposed by international organizations between pupil’s home and school. The p-median problem is a location-allocation problem that takes into account the average (total) distance between demand points (pupil’s home) and facility (pupil’s school). The p-median problem is used to determine the best location to place a limited number of schools. The model has been enhanced and applied to a wide range of school location problems in suburbs. After collecting necessary numerical data to each EDI, a formulation is presented and computational results are carried out.

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F. Ndiaye, B. Ndiaye and I. Ly, "Application of the p-Median Problem in School Allocation," American Journal of Operations Research, Vol. 2 No. 2, 2012, pp. 253-259. doi: 10.4236/ajor.2012.22030.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Z. Drezner, “Facility Location: A Survey of Applications and Methods,” Springer-Verlag, New York, 1995.
[2] M. R. Nooradelena and A. G. Noraida, “An Application of the p-Median Problem with Uncertainty in demand in Emergency Medical Services,” Proceedings of the 2nd IMT-GT Regional Conference on Mathematics, Statistics and Applications, Universiti Sains Malaysia, Penang, 13-15 June 2006.
[3] S. L. Hakimi, “Optimization Locations of Switching Centers and the Absolute Centers and Medians of a Graph,” Operations Research, Vol. 12, No. 3, 1964, pp. 450-459. doi:10.1287/opre.12.3.450
[4] R. Honey, G. Rushton, P. Lononis, B. Dalziel, M. Armstrong, S. De and P. Densham, “Stages in the Adoption of a Spatial Decision Support System for Reorganizing Service Delivery Regions,” Environment and Planning C, Vol. 9, No. 1, 1991, pp. 51-63. doi:10.1068/c090051
[5] D. Willer, “A Spatial Decision Support System for Bank Location: A Case Study,” NCGIA Technical Report, Vol. 90, No. 9, 1990.
[6] P. Chardaire and J. L. Lutton, “Using Simulated Annealing to Solve Concentrator Location Problems in Telecommunication Networks,” In: R. V. Vidal, Ed., Applied Simulated Annealing, Springer, Berlin, 1993, pp. 175-199. doi:10.1007/978-3-642-46787-5_9
[7] P. Densham and G. Rushton, “A More Efficient Heuristic for Solving Large p-Median Problems,” Papers in Regional Science, Vol. 71, 1996, pp. 307-329.
[8] R. L. Church and C. S. ReVelle, “The Maximal Covering Location Problem,” Papers in Regional Science, Vol. 32, No. 1, 1974, pp. 101-118. doi:10.1007/BF01942293
[9] IBM ILOG CPLEX Optimization Studio V12.3, Inc., “Using the CPLEXR Callable Library and CPLEX Barrier and Mixed Integer Solver Options,” 2011.
[10] A. G. Seye, “School Map Office,” Department of National Education in Senegal, 2009.
[11] F. Ndiaye, “Surveys of District Mayors, Municipal Agents, Heads of Establishments Involved in EDI of Guediawaye,” 2010.

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