A Web-Based Decision Support System for the Multiple Capacitated Facility Location Problem

  • Jason Papathanasiou
  • Nikolaos PloskasEmail author
  • Nikolaos Samaras
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 184)


The facility location problem is a widely studied classical operations research problem. To address this problem we implement an algorithm that calculates the exact solution for a given multiple capacitated facility location problem so long as that exists. Many issues of this problem belong to the NP-hard class of algorithms and as a result the computation time is disappointing for large networks. Therefore, we present a dynamic approximation algorithm for the solution of this problem that is capable to compute an approximation solution in an acceptable time interval. The aforementioned algorithms are integrated in a web-based Decision Support System (DSS). The DSS offers the possibility to create either a random or a custom graph and to evaluate both algorithms by performing alternative scenarios for the future development of the market. Finally, the DSS can export the results of the evaluation to a Microsoft Word document for further use.


Decision Support Systems Capacitated facility location problem Location allocation problem 


  1. 1.
    Brandeau, M.L., Chiu, S.S.: An overview of representative problems in location research. Manag. Sci. 35(6), 645–674 (1989)CrossRefzbMATHMathSciNetGoogle Scholar
  2. 2.
    Daskin, M.S.: Network and Discrete Location: Models, Algorithms, and Applications. Wiley, New York (1995)CrossRefzbMATHGoogle Scholar
  3. 3.
    Drezner, Z., Hamacher, H.W.: Facility Location: Theory and Algorithms. Springer, Berlin (2001)Google Scholar
  4. 4.
    Marianov, V., Serra, D.: Location problems in the public sector. In: Drezner, Z., Hamacher, H.W. (eds.) Facility Location: Applications and Theory. Springer, Berlin (2002)Google Scholar
  5. 5.
    Melo, M., Nickel, S., Saldanha da Gama, F.: Facility location and supply chain management - a review. Eur. J. Oper. Res. 196(2), 401–412 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
  6. 6.
    Revelle, C., Eiselt, H., Daskin, M.S.: A bibliography for some fundamental problem categories in discrete location science. Eur. J. Oper. Res. 184(3), 817–848 (2008)CrossRefzbMATHMathSciNetGoogle Scholar
  7. 7.
    Aboolian, R., Berman, O., Krass, D.: Competitive facility location and design problem. Eur. J. Oper. Res. 182(1), 40–62 (2007)CrossRefzbMATHMathSciNetGoogle Scholar
  8. 8.
    Drezner, T., Drezner, Z., Salhi, S.: Solving the multiple competitive facilities location problem. Eur. J. Oper. Res. 142, 138–151 (2002)CrossRefzbMATHMathSciNetGoogle Scholar
  9. 9.
    Plastria, F.: Static competitive facility location: an overview of optimization approaches. Eur. J. Oper. Res. 129, 461–470 (2001)CrossRefzbMATHMathSciNetGoogle Scholar
  10. 10.
    Aardal, K.: Capacitated facility location: separation algorithm and computational experience. Math. Program. 81, 149–175 (1998)zbMATHMathSciNetGoogle Scholar
  11. 11.
    Owen, S.H., Daskin, M.S.: Strategic facility location: a review. Eur. J. Oper. Res. 111, 423–447 (1998)CrossRefzbMATHGoogle Scholar
  12. 12.
    Sridharan, R.: Invited review the capacitated plant location problem. Eur. J. Oper. Res. 87, 203–213 (1995)CrossRefzbMATHGoogle Scholar
  13. 13.
    Avella, P., Boccia, M., Sforza, A., Vasilev, I.: An effective heuristic for large-scale capacitated facility location problems. J. Heuristics 15, 597–615 (2009)CrossRefzbMATHGoogle Scholar
  14. 14.
    Beasley, J.E.: Lagrangean heuristics for location problems. Eur. J. Operat. Res. 65, 383–399 (1993)CrossRefzbMATHGoogle Scholar
  15. 15.
    Chudak, F.A., Williamson, D.P.: Improved approximation algorithms for capacitated facility location problems. In: Cornuéjols, G., Burkard, R.E., Woeginger, G.J. (eds.) IPCO 1999. LNCS, vol. 1610, pp. 99–113. Springer, Heidelberg (1999) CrossRefGoogle Scholar
  16. 16.
    Cornuejols, G., Sridharan, R., Thizy, J.M.: A comparison of heuristics and relaxations for the capacitated plant location problem. Eur. J. Oper. Res. 50, 280–297 (1991)CrossRefzbMATHGoogle Scholar
  17. 17.
    Korupolu, M., Plaxton, C., Rajaraman, R.: Analysis of a local search heuristic for facility location problems. J. Algorithms 37, 146–188 (2000)CrossRefzbMATHMathSciNetGoogle Scholar
  18. 18.
    Kuehn, A.A., Hamburger, M.J.: A heuristic program for locating warehouses. Manag. Sci. 9, 643–666 (1963)CrossRefGoogle Scholar
  19. 19.
    Shonwiller, J., Harris, T.: Rural retail business thresholds and interdependencies. J. Reg. Sci. 21, 189–198 (1996)Google Scholar
  20. 20.
    Serra, D., Revelle, C., Rosing, K.: Surviving in a competitive spatial market: the threshold Capture Model. J. Reg. Sci. 4(39), 637–652 (1999)CrossRefGoogle Scholar
  21. 21.
    Shiode, S., Drezner, Z.: A competitive facility location problem on a tree network with stochastic weights. Eur. J. Oper. Res. 149, 47–52 (2003)CrossRefzbMATHMathSciNetGoogle Scholar
  22. 22.
    Papathanasiou, J., Manos, B.: An approximation algorithm for the location of dairy enterprises under time constraints. Eur. J. Oper. Res. 182(3), 1479–1487 (2007)CrossRefzbMATHGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Jason Papathanasiou
    • 1
  • Nikolaos Ploskas
    • 1
    Email author
  • Nikolaos Samaras
    • 1
  1. 1.University of MacedoniaThessalonikiGreece

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