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Lagrangian solution of maximum dispersion problems

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  • Şenay Ağca
  • Burak Eksioglu
  • Jay B. Ghosh

Abstract

We address the so‐called maximum dispersion problems where the objective is to maximize the sum or the minimum of interelement distances amongst a subset chosen from a given set. The problems arise in a variety of contexts including the location of obnoxious facilities, the selection of diverse groups, and the identification of dense subgraphs. They are known to be computationally difficult. In this paper, we propose a Lagrangian approach toward their solution and report the results of an extensive computational experimentation. Our results show that our Lagrangian approach is reasonably fast, that it yields heuristic solutions which provide good lower bounds on the optimum solution values for both the sum and the minimum problems, and further that it produces decent upper bounds in the case of the sum problem. For the sum problem, the results also show that the Lagrangian heuristic compares favorably against several existing heuristics. © 2000 John Wiley & Sons, Inc. Naval Research Logistics 47: 97–114, 2000

Suggested Citation

  • Şenay Ağca & Burak Eksioglu & Jay B. Ghosh, 2000. "Lagrangian solution of maximum dispersion problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 47(2), pages 97-114, March.
  • Handle: RePEc:wly:navres:v:47:y:2000:i:2:p:97-114
    DOI: 10.1002/(SICI)1520-6750(200003)47:23.0.CO;2-2
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    References listed on IDEAS

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    1. Erkut, Erhan & Neuman, Susan, 1989. "Analytical models for locating undesirable facilities," European Journal of Operational Research, Elsevier, vol. 40(3), pages 275-291, June.
    2. Marshall L. Fisher, 1981. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 27(1), pages 1-18, January.
    3. Mingers, J. & O'Brien, F. A., 1995. "Creating student groups with similar characteristics: A heuristic approach," Omega, Elsevier, vol. 23(3), pages 313-321, June.
    4. Weitz, R. R. & Lakshminarayanan, S., 1997. "An empirical comparison of heuristic and graph theoretic methods for creating maximally diverse groups, VLSI design, and exam scheduling," Omega, Elsevier, vol. 25(4), pages 473-482, August.
    5. S. S. Ravi & D. J. Rosenkrantz & G. K. Tayi, 1994. "Heuristic and Special Case Algorithms for Dispersion Problems," Operations Research, INFORMS, vol. 42(2), pages 299-310, April.
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    Cited by:

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    2. Juan F. Gomez & Anna Martínez-Gavara & Javier Panadero & Angel A. Juan & Rafael Martí, 2024. "A Forward–Backward Simheuristic for the Stochastic Capacitated Dispersion Problem," Mathematics, MDPI, vol. 12(6), pages 1-22, March.
    3. Martí, Rafael & Martínez-Gavara, Anna & Pérez-Peló, Sergio & Sánchez-Oro, Jesús, 2022. "A review on discrete diversity and dispersion maximization from an OR perspective," European Journal of Operational Research, Elsevier, vol. 299(3), pages 795-813.
    4. Parreño, Francisco & Álvarez-Valdés, Ramón & Martí, Rafael, 2021. "Measuring diversity. A review and an empirical analysis," European Journal of Operational Research, Elsevier, vol. 289(2), pages 515-532.
    5. Lixin Tang & Gongshu Wang & Jiyin Liu & Jingyi Liu, 2011. "A combination of Lagrangian relaxation and column generation for order batching in steelmaking and continuous‐casting production," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(4), pages 370-388, June.

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