In this paper, multidimensional test problems for methodssolving constrained Lipschitz global optimization problems are proposed. A new class of GKLS-based multidimensional test problems with continuously differentiable multiextremal objective functions and non-linearconstraints is described. In these constrained problems, the global minimizer does not coincide with the global minimizer of the respective unconstrained test problem, and is always located on the boundaries of the admissible region. Two types of constraints are introduced. The possibility to choose the difficulty of the admissible region is available.

Emmental-type GKLS-based multiextremal smooth test problems with non-linear constraints

Sergeev Yaroslav;Kvasov Dmitry;Mukhametzhanov Marat
2017-01-01

Abstract

In this paper, multidimensional test problems for methodssolving constrained Lipschitz global optimization problems are proposed. A new class of GKLS-based multidimensional test problems with continuously differentiable multiextremal objective functions and non-linearconstraints is described. In these constrained problems, the global minimizer does not coincide with the global minimizer of the respective unconstrained test problem, and is always located on the boundaries of the admissible region. Two types of constraints are introduced. The possibility to choose the difficulty of the admissible region is available.
978-3-319-69403-0
Constrained global optimization, numerical comparison, benchmark problems
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11770/178255
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