In this article, multi-dimensional global optimization problems are considered, where the objective function is supposed to be Lipschitz continuous, multiextremal and without a known analytic expression (black-box). Non-Univalent approximation of Peano curve to reduce the problem to a univariate one satisfying the Hölder condition is employed. Geometric frameworks for construction of global optimization algorithms are discussed. Numerical experiments executed on 100 test functions taken from the literature show a promising performance of the algorithms.

Non-Univalent Approximation of Peano Curve for Global Optimization

Daniela Lera
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Abstract

In this article, multi-dimensional global optimization problems are considered, where the objective function is supposed to be Lipschitz continuous, multiextremal and without a known analytic expression (black-box). Non-Univalent approximation of Peano curve to reduce the problem to a univariate one satisfying the Hölder condition is employed. Geometric frameworks for construction of global optimization algorithms are discussed. Numerical experiments executed on 100 test functions taken from the literature show a promising performance of the algorithms.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/324774
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