The Fermat—Weber location problem revisited
 J. Brimberg
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The Fermat—Weber location problem requires finding a point in ℝ^{ N } that minimizes the sum of weighted Euclidean distances tom given points. A onepoint iterative method was first introduced by Weiszfeld in 1937 to solve this problem. Since then several research articles have been published on the method and generalizations thereof. Global convergence of Weiszfeld's algorithm was proven in a seminal paper by Kuhn in 1973. However, since them given points are singular points of the iteration functions, convergence is conditional on none of the iterates coinciding with one of the given points. In addressing this problem, Kuhn concluded that whenever them given points are not collinear, Weiszfeld's algorithm will converge to the unique optimal solution except for a denumerable set of starting points. As late as 1989, Chandrasekaran and Tamir demonstrated with counterexamples that convergence may not occur for continuous sets of starting points when the given points are contained in an affine subspace of ℝ^{ N }. We resolve this open question by proving that Weiszfeld's algorithm converges to the unique optimal solution for all but a denumerable set of starting points if, and only if, the convex hull of the given points is of dimensionN.
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 Title
 The Fermat—Weber location problem revisited
 Journal

Mathematical Programming
Volume 71, Issue 1 , pp 7176
 Cover Date
 19951101
 DOI
 10.1007/BF01592245
 Print ISSN
 00255610
 Online ISSN
 14364646
 Publisher
 SpringerVerlag
 Additional Links
 Topics
 Keywords

 Location theory
 Fermat—Weber problem
 Weiszfeld's iterative algorithm
 Industry Sectors
 Authors

 J. Brimberg ^{(1)}
 Author Affiliations

 1. Department of Engineering Management, Royal Military College of Canada, K7K 5L0, Kingston, Ontario, Canada