ISSN:
1436-4646
Keywords:
Minimax Problems
;
Minisum Problems
;
Nondifferentiable Optimization
;
Subgradients
;
Location Problems
;
Linear Approximation Problems
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract We present a subgradient algorithm for minimizing the maximum of a finite collection of functions. It is assumed that each function is the sum of a finite collection of basic convex functions and that the number of different subgradient sets associated with nondifferentiable points of each basic function is finite on any bounded set. Problems belonging to this class include the linear approximation problem and both the minimax and minisum problems of location theory. Convergence of the algorithm to an epsilon-optimal solution is proven and its effectiveness is demonstrated by solving a number of location problems and linear approximation problems.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01609012
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