2024-03-29T10:24:44Zhttps://uvadoc.uva.es/oai/requestoai:uvadoc.uva.es:10324/573212022-11-22T20:00:59Zcom_10324_966com_10324_952com_10324_894col_10324_967
A direct search algorithm for global optimization
Baeyens Lázaro, Enrique
Herreros López, Alberto
Perán, José
Producción Científica
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.
2022-11-22
2022-11-22
2016
info:eu-repo/semantics/article
Algorithms, 2016, vol. 9, n. 2, p. 40
https://uvadoc.uva.es/handle/10324/57321
10.3390/a9020040
40
2
Algorithms
9
1999-4893
eng
https://www.mdpi.com/1999-4893/9/2/40
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
© 2016 The Author(s)
Atribución 4.0 Internacional
MDPI