Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/57321
Título
A direct search algorithm for global optimization
Año del Documento
2016
Editorial
MDPI
Descripción
Producción Científica
Documento Fuente
Algorithms, 2016, vol. 9, n. 2, p. 40
Abstract
A direct search algorithm is proposed for minimizing an arbitrary real valued function. The algorithm uses a new function transformation and three simplex-based operations. The function transformation provides global exploration features, while the simplex-based operations guarantees the termination of the algorithm and provides global convergence to a stationary point if the cost function is differentiable and its gradient is Lipschitz continuous. The algorithm’s performance has been extensively tested using benchmark functions and compared to some well-known global optimization algorithms. The results of the computational study show that the algorithm combines both simplicity and efficiency and is competitive with the heuristics-based strategies presently used for global optimization.
Materias Unesco
33 Ciencias Tecnológicas
12 Matemáticas
Palabras Clave
Global optimization
Direct search methods
Search space transformation
Revisión por pares
SI
DOI
Version del Editor
Propietario de los Derechos
© 2016 The Author(s)
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
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