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An Analysis of Network Location Problems with Distance Constraints


  • I. Douglas Moon

    (Rutgers, The State University of New Jersey, Newark)

  • Sohail S. Chaudhry

    (Columbia University)


This paper concerns a class of network location problems with minimum or maximum separation requirements between (uncapacitated) facilities or between demand points and the facilities, or both. Its purpose is three-fold. First, it is to recognize distance constraints as increasing real life restrictions through various motivating illustrations. Using a new classification scheme, the paper introduces a variety of distance-constrained problems defined in a unified manner. These include a number of new problems. Second, it is to survey existing solution techniques, available only for a few of such constrained problems. Finally, it is to shed some light on yet unstudied problems by exploring possible extensions of some of the known solution techniques or discussing varying degrees of difficulties involved. In particular, the paper presents integer programming formulations of several new problems along with the results of applying linear programming relaxation methods. Although the computational experience is somewhat disappointing for some of these problems, the results provide greater insight into the problems. With the stated purpose, it is hoped that this paper will stimulate future research in this important problem area.

Suggested Citation

  • I. Douglas Moon & Sohail S. Chaudhry, 1984. "An Analysis of Network Location Problems with Distance Constraints," Management Science, INFORMS, vol. 30(3), pages 290-307, March.
  • Handle: RePEc:inm:ormnsc:v:30:y:1984:i:3:p:290-307

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    References listed on IDEAS

    1. Ian I. Mitroff, 1972. "The Myth of Objectivity OR Why Science Needs a New Psychology of Science," Management Science, INFORMS, vol. 18(10), pages 613-618, June.
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    Cited by:

    1. Murray, Alan T. & Church, Richard L., 1997. "Facets for node packing," European Journal of Operational Research, Elsevier, vol. 101(3), pages 598-608, September.
    2. repec:eee:ecomod:v:214:y:2008:i:2:p:284-292 is not listed on IDEAS
    3. Niblett, Matthew R. & Church, Richard L., 2015. "The disruptive anti-covering location problem," European Journal of Operational Research, Elsevier, vol. 247(3), pages 764-773.
    4. ReVelle, C. S. & Eiselt, H. A., 2005. "Location analysis: A synthesis and survey," European Journal of Operational Research, Elsevier, vol. 165(1), pages 1-19, August.
    5. Sayyady, Fatemeh & Fathi, Yahya, 2016. "An integer programming approach for solving the p-dispersion problem," European Journal of Operational Research, Elsevier, vol. 253(1), pages 216-225.
    6. Lei, Ting L. & Church, Richard L., 2015. "On the unified dispersion problem: Efficient formulations and exact algorithms," European Journal of Operational Research, Elsevier, vol. 241(3), pages 622-630.
    7. Paul, Nicholas R. & Lunday, Brian J. & Nurre, Sarah G., 2017. "A multiobjective, maximal conditional covering location problem applied to the relocation of hierarchical emergency response facilities," Omega, Elsevier, vol. 66(PA), pages 147-158.
    8. Erkut, E. & ReVelle, C. & Ulkusal, Y., 1996. "Integer-friendly formulations for the r-separation problem," European Journal of Operational Research, Elsevier, vol. 92(2), pages 342-351, July.
    9. Averbakh, Igor & Berman, Oded, 1996. "Locating flow-capturing units on a network with multi-counting and diminishing returns to scale," European Journal of Operational Research, Elsevier, vol. 91(3), pages 495-506, June.
    10. Prokopyev, Oleg A. & Kong, Nan & Martinez-Torres, Dayna L., 2009. "The equitable dispersion problem," European Journal of Operational Research, Elsevier, vol. 197(1), pages 59-67, August.
    11. Welch, S. B. & Salhi, S., 1997. "The obnoxious p facility network location problem with facility interaction," European Journal of Operational Research, Elsevier, vol. 102(2), pages 302-319, October.
    12. Batta, Rajan & Lejeune, Miguel & Prasad, Srinivas, 2014. "Public facility location using dispersion, population, and equity criteria," European Journal of Operational Research, Elsevier, vol. 234(3), pages 819-829.


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