Skip to main content
Log in

Sequential location of two facilities: comparing random to optimal location of the first facility

  • Published:
Annals of Operations Research Aims and scope Submit manuscript

Abstract

We investigate sequential location of two facilities. One strategy is to locate the first facility at its single facility optimum. A second strategy is to randomly locate the first facility. The second facility is then located at its optimal location given the first facility’s location. We investigate which of these two strategies is better. Three objectives are tested: minisum, minimax, and competitive. We considered three environments: uniform demand in a square, discrete demand in the plane, and demand at nodes of a network. For the competitive objective we obtained what might be considered the expected result of locating the first facility optimally is better. For the minisum and minimax objectives, we found a surprising result: it is better to locate the first facility at random. We investigate the reasons behind these results which support the principle of add-heuristics and the greedy randomized adaptive search procedure where the search does not necessarily select the best solution in a greedy sequential approach.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Abramowitz, M., & Stegun, I. (1972). Handbook of mathematical functions. New York, NY: Dover Publications.

    Google Scholar 

  • Al-Khayyal, F., Tuy, H., & Zhou, F. (2002). Large-scale single facility continuous location by D.C. optimization. Optimization, 51, 271–292.

    Article  Google Scholar 

  • Alexandroff, A. D. (1950). Surfaces represented by the difference of convex functions. Doklady Akademii Nauk SSSR (N.S.), 72, 613–616.

  • Berman, O., & Drezner, Z. (2008). A new formulation for the conditional p-median and p-center problems. Operations Research Letters, 36, 481–483.

    Article  Google Scholar 

  • Berman, O., & Simchi-Levi, D. (1990). The conditional location problem on networks. Transportation Science, 24, 77–78.

    Article  Google Scholar 

  • Blanquero, R., & Carrizosa, E. (2009). Continuous location problems and big triangle small triangle: Constructing better bounds. Journal of Global Optimization, 45, 389–402.

    Article  Google Scholar 

  • Chen, P. C., Hansen, P., Jaumard, B., & Tuy, H. (1998). A fast algorithm for the greedy interchange for large-scale clustering and median location problems by D.-C. programming. Operations Research, 46, 548–562.

    Article  Google Scholar 

  • Chen, R. (1988). Conditional minisum and minimax location-allocation problems in euclidean space. Transportation Science, 22, 158–160.

    Google Scholar 

  • Chen, R., & Handler, G. Y. (1993). The conditional \(p\)-center in the plane. Naval Research Logistics, 40, 117–127.

    Article  Google Scholar 

  • Cooper, L. (1963). Location-allocation problems. Operations Research, 11, 331–343.

    Article  Google Scholar 

  • Cooper, L. (1964). Heuristic methods for location-allocation problems. SIAM Review, 6, 37–53.

    Article  Google Scholar 

  • Current, J., Daskin, M., & Schilling, D. (2002). Discrete network location models. In Z. Drezner & H. W. Hamacher (Eds.), Facility location: Applications and theory (pp. 81–118). Berlin: Springer.

    Chapter  Google Scholar 

  • Current, J., Ratick, S., & ReVelle, C. (1998). Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach. European Journal of Operational Research, 110, 597–609.

    Article  Google Scholar 

  • Drezner, T. (1994). Optimal continuous location of a retail facility, facility attractiveness, and market share: An interactive model. Journal of Retailing, 70, 49–64.

    Article  Google Scholar 

  • Drezner, T. (2011). Cannibalization in a competitive environment. International Regional Science Review, 34, 306–322.

    Article  Google Scholar 

  • Drezner, Z. (1984). The planar two-center and two-median problems. Transportation Science, 18, 351–361.

    Article  Google Scholar 

  • Drezner, Z. (1995). Dynamic facility location: The progressive p-median problem. Location Science, 3, 1–7.

    Article  Google Scholar 

  • Drezner, Z. (1996). A note on accelerating the Weiszfeld procedure. Location Science, 3, 275–279.

    Article  Google Scholar 

  • Drezner, Z. (2006). Finding a cluster of points and the grey pattern quadratic assignment problem. OR Spectrum, 28, 417–436.

    Article  Google Scholar 

  • Drezner, Z. (2007). A general global optimization approach for solving location problems in the plane. Journal of Global Optimization, 37, 305–319.

    Article  Google Scholar 

  • Drezner, Z. (2013). The fortified Weiszfeld algorithm for solving the Weber problem. IMA Journal of Management Mathematics. doi: 10.1093/imaman/dpt019.

  • Drezner, Z., Klamroth, K., Schöbel, A., & Wesolowsky, G. O. (2002). The Weber problem. In Z. Drezner & H. W. Hamacher (Eds.), Facility location: Applications and theory (pp. 1–36). Berlin: Springer.

    Chapter  Google Scholar 

  • Drezner, Z., & Suzuki, A. (2004). The big triangle small triangle method for the solution of non-convex facility location problems. Operations Research, 52, 128–135.

    Article  Google Scholar 

  • Drezner, Z., & Wesolowsky, G. O. (1991). Facility location when demand is time dependent. Naval Research Logistics, 38, 763–777.

    Article  Google Scholar 

  • Eiselt, H. A., & Laporte, G. (1997). Sequential location problems. European Journal of Operational Research, 96, 217–231.

    Article  Google Scholar 

  • Elzinga, J., & Hearn, D. (1972). Geometrical solutions for some minimax location problems. Transportation Science, 6, 379–394.

    Article  Google Scholar 

  • Ghosh, A., & Craig, C. S. (1991). FRANSYS: A franchise location model. Journal of Retailing, 67, 212–234.

    Google Scholar 

  • Ghosh, A., & Rushton, G. (1987). Spatial analysis and location-allocation models. New York, NY: Van Nostrand Reinhold Company.

    Google Scholar 

  • Hakimi, S. L. (1964). Optimum locations of switching centres and the absolute centres and medians of a graph. Operations Research, 12, 450–459.

    Article  Google Scholar 

  • Hakimi, S. L. (1965). Optimum distribution of switching centers in a communication network and some related graph theoretic problems. Operations Research, 13, 462–475.

    Article  Google Scholar 

  • Hansen, P., Peeters, D., & Thisse, J.-F. (1981). On the location of an obnoxious facility. Sistemi Urbani, 3, 299–317.

    Google Scholar 

  • Hartman, P. (1959). On functions representable as a difference of convex functions. Pacific Journal of Mathematics, 9, 707–713.

    Article  Google Scholar 

  • Horst, R., Phong, T. Q., Thoai, N. V., & de Vries, J. (1991). On solving a d.c. programming problem by a sequence of linear programs. Journal of Global Optimization, 1, 183–203.

    Article  Google Scholar 

  • Huff, D. L. (1964). Defining and estimating a trade area. Journal of Marketing, 28, 34–38.

    Article  Google Scholar 

  • Huff, D. L. (1966). A programmed solution for approximating an optimum retail location. Land Economics, 42, 293–303.

    Article  Google Scholar 

  • Ignizio, J. P. (1980). Solving large-scale problems: A venture into a new dimension. Journal of the Operational Research Society, 31, 217–225.

  • Kariv, O. & Hakimi, S. L. (1979a). An algorithmic approach to network location problems. I: The p-centers. SIAM Journal on Applied Mathematics, 37, 513–538.

  • Kariv, O., & Hakimi, S. L. (1979b). An algorithmic approach to network location problems. II: The p-medians. SIAM Journal on Applied Mathematics, 37, 539–560.

  • Klincewicz, J. G. & Luss, H. (1986). A lagrangian relaxation heuristic for capacitated facility location with single-source constraints. Journal of the Operational Research Society, 37, 495–500.

  • Li, Y., Pardalos, P. M., & Resende, M. G. C. (1994). A greedy randomized adaptive search procedure for the quadratic assignment problem. In P. M. Pardalos & H. Wolkowicz (Eds.), Quadratic assignment and related problems, DIMACS series in discrete mathematics and theoretical computer science (Vol. 16, pp. 237–261). Providence, RI: American Mathematical Society.

    Google Scholar 

  • Maranas, C. D., & Floudas, C. A. (1993). A global optimization method for Weber’s problem with attraction and repulsion. In W. W. Hager, D. W. Hearn, & P. M. Pardalos (Eds.), Large scale optimization: State of the art (pp. 259–293). Dordrecht: Kluwer.

    Google Scholar 

  • Minieka, E. (1980). Conditional centers and medians on a graph. Networks, 10, 265–272.

    Article  Google Scholar 

  • Ogilvy, C. S. (1990). Excursions in geometry. New York, NY: Dover Publications.

    Google Scholar 

  • Okabe, A., Boots, B., Sugihara, K., & Chiu, S. N. (2000). Spatial tessellations: Concepts and applications of Voronoi diagrams. New York, NY: Wiley Series in Probability and Statistics, Wiley.

    Book  Google Scholar 

  • Plastria, F. (1992). GBSSS, the generalized big square small square method for planar single facility location. European Journal of Operational Research, 62, 163–174.

    Article  Google Scholar 

  • Plastria, F. (2005). Avoiding cannibalisation and/or competitor reaction in planar single facility location. Journal of the Operational Research Society of Japan, 48, 148–157.

    Google Scholar 

  • Schöbel, A., & Scholz, D. (2010). The big cube small cube solution method for multidimensional facility location problems. Computers and Operations Research, 37, 115–122.

    Article  Google Scholar 

  • Stackelberg, H. V. (1934). Marktform und Gleichgewicht. Vienne: Julius Springer.

    Google Scholar 

  • Suzuki, A., & Drezner, Z. (1996). The p-center location problem in an area. Location Science, 4, 69–82.

    Article  Google Scholar 

  • Suzuki, A., & Okabe, A. (1995). Using Voronoi diagrams. In Z. Drezner (Ed.), Facility location: A survey of applications and methods (pp. 103–118). New York: Springer.

    Chapter  Google Scholar 

  • Szabo, P. G., Markot, M., Csendes, T., & Specht, E. (2007). New approaches to circle packing in a square: With program codes. New York: Springer.

    Google Scholar 

  • Toth, B., Fernandez, J., Pelegrin, B., & Plastria, F. (2009). Sequential versus simultaneous approach in the location and design of two new facilities using planar Huff-like models. Computers and Operations Research, 36, 1393–1405.

    Article  Google Scholar 

  • Tuy, H., Al-Khayyal, F., & Zhou, F. (1995). A D.C. optimization method for single facility location problems. Journal of Global Optimization, 7, 209–227.

    Article  Google Scholar 

  • Weiszfeld, E. (1936). Sur le point pour lequel la somme des distances de n points donnes est minimum. Tohoku Mathematical Journal, 43, 355–386.

    Google Scholar 

  • Weiszfeld, E. & Plastria, F. (2009). On the point for which the sum of the distances to n given points is minimum. Annals of Operations Research, 167, 7–41. (English Translation of Weiszfeld [54]).

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zvi Drezner.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Drezner, T., Drezner, Z. Sequential location of two facilities: comparing random to optimal location of the first facility. Ann Oper Res 246, 5–18 (2016). https://doi.org/10.1007/s10479-014-1699-y

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10479-014-1699-y

Keywords

Navigation