ISSN:
1573-2878
Keywords:
Global optimization
;
nondifferentiable optimization
;
Lipschitz continuous functions
;
outer-approximation algorithms
Source:
Springer Online Journal Archives 1860-2000
Topics:
Mathematics
Notes:
Abstract It is known that the problem of minimizing a convex functionf(x) over a compact subsetX of ℝ n can be expressed as minimizing max{g(x, y)|y ∈X}, whereg is a support function forf[f(x) ≥g(x, y), for ally ∈X andf(x)=g(x, x)]. Standard outer-approximation theory can then be employed to obtain outer-approximation algorithms with procedures for dropping previous cuts. It is shown here how this methodology can be extended to nonconvex nondifferentiable functions.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00934131
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