Stochastic Smoothing Methods for Nonsmooth Global Optimization

Stochastic Smoothing Methods for Nonsmooth Global Optimization

Abstract. The paper presents the results of testing the stochastic smoothing method for global optimization of a multiextremal function in a convex feasible subset of Euclidean space. Preliminarily, the objective function is extended outside the admissible region so that its global minimum does not...

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Bibliografiska uppgifter
Huvudupphovsman:	V.I. Norkin
Materialtyp:	Artikel
Språk:	English
Publicerad:	V.M. Glushkov Institute of Cybernetics 2020-03-01
Serie:	Кібернетика та комп'ютерні технології
Ämnen:	global optimization steklov smoothing averaged functions stochastic optimization nonsmooth nonconvex optimization
Länkar:	http://cctech.org.ua/13-vertikalnoe-menyu-en/89-abstract-20-1-1-arte

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