Skip to main content
Log in

A two-level evolutionary algorithm for solving the facility location and design (1|1)-centroid problem on the plane with variable demand

  • Published:
Journal of Global Optimization Aims and scope Submit manuscript

Abstract

In this work, the problem of a company or chain (the leader) that considers the reaction of a competitor chain (the follower) is studied. In particular, the leader wants to set up a single new facility in a planar market where similar facilities of the follower, and possibly of its own chain, are already present. The follower will react by locating another single facility after the leader locates its own facility. Both the location and the quality (representing design, quality of products, prices, etc.) of the new leader’s facility have to be found. The aim is to maximize the profit obtained by the leader considering the future follower’s entry. The demand is supposed to be concentrated at n demand points. Each demand point splits its buying power among the facilities proportionally to the attraction it feels for them. The attraction of a demand point for a facility depends on both the location and the quality of the facility. Usually, the demand is considered in the literature to be fixed or constant regardless the conditions of the market. In this paper, the demand varies depending on the attraction for the facilities. Taking variable demand into consideration makes the model more realistic. However, it increases the complexity of the problem and, therefore, the computational effort needed to solve it. Three heuristic methods are proposed to cope with this hard-to-solve global optimization problem, namely, a grid search procedure, a multistart algorithm and a two-level evolutionary algorithm. The computational studies show that the evolutionary algorithm is both the most robust algorithm and the one that provides the best results.

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.

Similar content being viewed by others

References

  1. Drezner Z.: Facility Location: A Survey of Applications and Methods. Springer Series in Operations Research and Financial Engineering, Berlin (1995)

    Book  Google Scholar 

  2. Drezner Z., Hamacher H.W.: Facility location. Applications and Theory. Springer, Berlin (2002)

    Book  Google Scholar 

  3. Eiselt H.A., Laporte G., Thisse J.F.: Competitive location models: a framework and bibliography. Transport. Sci. 27(1), 44–54 (1993)

    Article  Google Scholar 

  4. Kilkenny M., Thisse J.F.: Economics of location: a selective survey. Comput. Oper. Res. 26(14), 1369–1394 (1999)

    Article  Google Scholar 

  5. Plastria F.: Static competitive facility location: an overview of optimisation approaches. Eur. J. Oper. Res. 129(3), 461–470 (2001)

    Article  Google Scholar 

  6. Eiselt H.A., Laporte G.: Sequential location problems. Eur. J. Oper. Res. 96(2), 217–231 (1997)

    Article  Google Scholar 

  7. Hotelling H.: Stability in competition. Econ. J. 39, 41–57 (1929)

    Article  Google Scholar 

  8. Hakimi S.L.: On locating new facilities in a competitive environment. Eur. J. Oper. Res. 12(1), 29–35 (1983)

    Article  Google Scholar 

  9. Drezner Z.: Competitive location strategies for two facilities. Reg. Sci. Urban Econ. 12(4), 485–493 (1982)

    Article  Google Scholar 

  10. Bhadury J., Eiselt H.A., Jaramillo J.H.: An alternating heuristic for medianoid and centroid problems in the plane. Comput. Oper. Res. 30(4), 553–565 (2003)

    Article  Google Scholar 

  11. Drezner T., Drezner Z.: Facility location in anticipation of future competition. Locat. Sci. 6(1), 155–173 (1998)

    Article  Google Scholar 

  12. Drezner T., Drezner Z.: Retail facility location under changing market conditions. IMA J. Manag. Math. 13(4), 283–302 (2002)

    Article  Google Scholar 

  13. Redondo J.L., Fernández J., García I., Ortigosa P.M.: Heuristics for the facility location and design (1|1)-centroid problem on the plane. Comput. Optim. Appl. 45(1), 111–141 (2010)

    Article  Google Scholar 

  14. Pardalos, P.M., Chinchuluun, A., Huang, H.X.: Multilevel (hierarchical) optimization: complexity issues, optimality conditions, algorithms. In: Gao D.Y., Sherali H.D. (eds) Advances in Applied Mathematics and Global Optimization in Honor of Gilbert Strang, Advances in Mechanics and mathematics. vol. 17, pp. 197–222 (2009)

  15. Pardalos P.M., Migdalas A., Värbrand P.: Multilevel Optimization: Algorithms and Applications. Kluwer, Dordrecht (1998)

    Google Scholar 

  16. Redondo J.L., Fernández J., Arrondo A.G., García I., Ortigosa P.M.: Fixed or variable demand? Does it matter when locating a facility?. Omega 40(1), 9–20 (2012)

    Article  Google Scholar 

  17. Jelásity M., Ortigosa P.M., García I.: UEGO, an abstract clustering technique for multimodal global optimization. J. Heuristics 7(3), 215–233 (2001)

    Article  Google Scholar 

  18. Fernández J., Pelegrín B., Plastria F., Tóth B.: Solving a Huff-like competitive location and design model for profit maximization in the plane. Eur. J. Oper. Res. 179(3), 1274–1287 (2007)

    Article  Google Scholar 

  19. Tóth B., Plastria F., Fernández J., Pelegrín B.: On the impact of spatial pattern, aggregation, and model parameters in planar huff-like competitive location and design problems. OR Spectr. 31(1), 601–627 (2009)

    Google Scholar 

  20. Berman O., Krass D.: Locating multiple competitive facilities: spatial interaction models with variable expenditures. Ann. Oper. Res. 111(1), 197–225 (2002)

    Article  Google Scholar 

  21. Tóth B., Fernández J.: Interval methods for single and bi-objective optimization problems—applied to competitive facility location problems. Lambert Academic Publishing, Saarbrücken (2010)

    Google Scholar 

  22. Speer, N., Spieth, C., Zell, A.: A memetic co-clustering algorithm for gene exression profiles and biological annotation. In: Proceedings of the IEEE 2004 Congress on Evolutionary Computation, CEC 2004, vol. 2, pp. 1631–1638. IEEE Press (2004)

  23. Solis F.J., Wets R.J.B.: Minimization by random search techniques. Math. Oper. Res. 6(1), 19–30 (1981)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to J. L. Redondo.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Redondo, J.L., Arrondo, A.G., Fernández, J. et al. A two-level evolutionary algorithm for solving the facility location and design (1|1)-centroid problem on the plane with variable demand. J Glob Optim 56, 983–1005 (2013). https://doi.org/10.1007/s10898-012-9893-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10898-012-9893-4

Keywords

Navigation