A primal—dual algorithm for the Fermat—Weber problem involving gauges
Mathematical Programming: Series A and B
Algebraic optimization: the Fermat-Weber location problem
Mathematical Programming: Series A and B
A note on the Weber location problem
Annals of Operations Research - Special issue on locational decisions
Asymptotic behavior of the Weber location problem on the plane
Annals of Operations Research - Special issue on locational decisions
The Fermat-Weber location problem revisited
Mathematical Programming: Series A and B
Duality theorem for a generalized Fermat-Weber problem
Mathematical Programming: Series A and B
A Newton Acceleration of the Weiszfeld Algorithm forMinimizing the Sum of Euclidean Distances
Computational Optimization and Applications
Directional Newton methods in n variables
Mathematics of Computation
Accelerating convergence in the Fermat-Weber location problem
Operations Research Letters
A heuristic method for large-scale multi-facility location problems
Computers and Operations Research
The Newton Bracketing method for the minimization of convex functions subject to affine constraints
Discrete Applied Mathematics
A semi-Lagrangian scheme for the game p-Laplacian via p-averaging
Applied Numerical Mathematics
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An iterative method for the minimization of convex functions {f}\,{:}\,{\bb R}^n \to {\bb R}, called a Newton Bracketing (NB) method, is presented. The NB method proceeds by using Newton iterations to improve upper and lower bounds on the minimum value. The NB method is valid for n = 1, and in some cases for n 1 (sufficient conditions given here). The NB method is applied to large scale Fermat–Weber location problems.