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A primal-dual algorithm for the fermat-weber problem involving mixed gauges

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Abstract

We give a new algorithm for solving the Fermat-Weber location problem involving mixed gauges. This algorithm, which is derived from the partial inverse method developed by J.E. Spingarn, simultaneously generates two sequences globally converging to a primal and a dual solution respectively. In addition, the updating formulae are very simple; a stopping rule can be defined though the method is not dual feasible and the entire set of optimal locations can be obtained from the dual solution by making use of optimality conditions.

When polyhedral gauges are used, we show that the algorithm terminates in a finite number of steps, provided that the set of optimal locations has nonepty interior and a counterexample to finite termination is given in a case where this property is violated. Finally, numerical results are reported and we discuss possible extensions of these results.

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References

  1. R.D. Armstrong, “A primal simplex algorithm to solve a rectilinear distance facility location problem,”Naval Research Logistics Quarterly 24 (1977) 619–626.

    MATH  Google Scholar 

  2. L. Cooper and I.N. Katz, “The Weber problem revisited,”Computers and Mathematics with Applications 7 (1981) 225–234.

    Article  MATH  MathSciNet  Google Scholar 

  3. P.H. Calamai and A.R. Conn, “A stable algorithm for solving the multifacility location problem involving Euclidean distances,”SIAM Journal on Scientific and Statistical Computing 1 (1980) 512–526.

    Article  MATH  MathSciNet  Google Scholar 

  4. P.H. Calamai and A.R. Conn, “A second order method for solving the continuous multifacility location problem,” in: G.A. Watson, ed.,Numerical Analysis: Proceedings of the Ninth Biennial Conference. Dundee, Scotland, Lecture Notes in Mathematics 912 (Springer-Verlag, Berlin, Heidelberg and New York, 1982), pp. 1–25.

    Google Scholar 

  5. F. Cordellier and J.C. Fiorot, “On the Fermat-Weber problem with convex cost functions,”Mathematical Programming 14 (1978) 295–311.

    Article  MATH  MathSciNet  Google Scholar 

  6. A. Dax, “The use of Newton's method for solving Euclidean multifacility location problems,” Tech. Report. Hydrological Service (Jerusalem, 1985).

    Google Scholar 

  7. P.D. Dowling and R.F. Love, “Bounding methods for facilities location algorithms,” Research and Working Paper Series No. 219, McMaster University (Hamilton, Ontario, 1984).

    Google Scholar 

  8. P.D. Dowling and R.F. Love, “An evaluation of the dual as a lower bound in facilities location problems,” Research and Working Paper Series No. 236, McMaster University (Hamilton, Ontario, 1985).

    Google Scholar 

  9. R. Durier, “On efficient points and Fermat-Weber problem,” Working Paper, Université de Bourgogne, (Dijon, France, 1984).

    Google Scholar 

  10. R. Durier, “Weighting factor results in vector optimization,” Working Paper, Université de Bourgogne (Dijon, France, 1984).

    Google Scholar 

  11. R. Durier and C. Michelot, “Geometrical properties of the Fermat-Weber problem,”European Journal of Operational Research 20 (1985) 332–343.

    Article  MATH  MathSciNet  Google Scholar 

  12. R. Durier and C. Michelot, “Sets of efficient points in a normed space,”Journal of Mathematical Analysis and Applications 117 (1986), 506–528.

    Article  MATH  MathSciNet  Google Scholar 

  13. U. Eckhardt, “Theorems on the dimension of convex sets,”Linear Algebra and its Applications 12 (1975) 63–76.

    Article  MATH  MathSciNet  Google Scholar 

  14. D.J. Elzinga and D.W. Hearn, “On stopping rules for facilities location algorithms,”IIE Transactions 15 (1983) 81–83.

    Google Scholar 

  15. R.L. Francis and J.M. Goldstein, “Location theory: A selective bibliography,”Operations Research 22 (1974) 400–410.

    MATH  MathSciNet  Google Scholar 

  16. R.L. Francis and J.A. White,Facility Layout and Location: An Analytical Approach (Prentice-Hall, Englewood Cliffs, NJ, 1974).

    Google Scholar 

  17. I.N. Katz, “Local convergence in Fermat's problem,”Mathematical Programming 6 (1974), 89–104.

    Article  MATH  MathSciNet  Google Scholar 

  18. H.W. Kuhn, “A note on Fermat's problem,”Mathematical Programming 4 (1973) 98–107.

    Article  MATH  MathSciNet  Google Scholar 

  19. H.W. Kuhn and R.E. Kuenne, “An efficient algorithm for the numerical solution of the generalized Weber problem in spatial economics”,Journal of Regional Science 4 (1962) 21–23.

    Article  Google Scholar 

  20. R.F. Love and W.Y. Yeong, “A stopping rule for facilities location algorithms,”AIIE Transactions 13 (1981) 357–362.

    MathSciNet  Google Scholar 

  21. L.M. Ostresch, “On the convergence of a class of iterative methods for solving the Weber location problem,”Operations Research 26 (1978) 597–609.

    MathSciNet  Google Scholar 

  22. L.M. Ostresh, “Convergence and descent in the Fermat location problem,”Transportation Science 12 (1978) 153–164.

    MathSciNet  Google Scholar 

  23. M.L. Overton, “A quadratically convergent method for minimizing a sum of Euclidean norms,”Mathematical Programming 27 (1983) 34–63.

    MATH  MathSciNet  Google Scholar 

  24. A. Planchart and A.P. Hurter, “An efficient algorithm for the solution of Weber problem with mixed norms,”SIAM Journal on Control 13 (1975) 650–665.

    Article  MATH  MathSciNet  Google Scholar 

  25. F. Plastria, “Continuous location problems solved by cutting planes,” Working Paper, Vrije Universiteit brussels, (Bruxelles, 1982).

    Google Scholar 

  26. R.T. RockafellarConvex Analysis, (Princeton University Press, Princeton, NJ, 1970).

    MATH  Google Scholar 

  27. R.T. Rockafellar, “Monotone operators and the proximal point algorithm,”SIAM Journal on Control and Optimization 14 (1976) 877–898.

    Article  MATH  MathSciNet  Google Scholar 

  28. J.E. Spingarn, “Partial inverse of a monotone operator,”Applied Mathematics and Optimization 10 (1983) 247–265.

    Article  MATH  MathSciNet  Google Scholar 

  29. J.E. Spingarn, “A primal-dual projection method for solving systems of linear inequalities,”Linear Algebra and its Applications 65 (1985) 45–62.

    Article  MATH  MathSciNet  Google Scholar 

  30. J.E. Ward and R.E. Wendell, “Using block norms for location modeling,”Operations Research 33 (1985) 1074–1090.

    Article  MATH  MathSciNet  Google Scholar 

  31. E. Weiszfeld, “Sur le point pour lequel la somme des distances den points donnés est minimum,”The Tôhoku Mathematical Journal 43 (1937) 355–386.

    MATH  Google Scholar 

  32. R.E. Wendell and E.L. Peterson, “A dual approach for obtaining lower bounds to the Weber problem,”Journal of Regional Science 24 (1984) 219–228.

    Article  Google Scholar 

  33. C. Witzgall, “Optimal location of a central facility: Mathematical models and Concepts,” National Bureau of Standards, Report 8388 (Washington, 1964).

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Michelot, C., Lefebvre, O. A primal-dual algorithm for the fermat-weber problem involving mixed gauges. Mathematical Programming 39, 319–335 (1987). https://doi.org/10.1007/BF02592080

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  • DOI: https://doi.org/10.1007/BF02592080

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