Abstract
Coming back to optimization problems of the type (1.1.8), i.e.,
, let us accept that the sought approximation to the global optimizer x* is x* N provided by the uniform grid technique (1.1.13)–(1.1.15) for some specified number N of trials. This assumption, which is quite natural due to the relation (1.1.17), reduces the continuous problem (2.1.1) to the discrete problem of finding the node x α of the uniform grid
, satisfying the inequalities
, where
.
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© 2000 Springer Science+Business Media Dordrecht
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Strongin, R.G., Sergeyev, Y.D. (2000). Global Optimization Algorithms as Statistical Decision Procedures — The Information Approach. In: Global Optimization with Non-Convex Constraints. Nonconvex Optimization and Its Applications, vol 45. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-4677-1_2
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DOI: https://doi.org/10.1007/978-1-4615-4677-1_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-7117-5
Online ISBN: 978-1-4615-4677-1
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