Articolo in rivista, 2023, ENG, 10.1007/s10957-022-02153-5
Bellavia S.; Gurioli G.; Morini B.; Toint P.L.
Dipartimento di Ingegneria Industriale, Università degli Studi di Firenze, Firenze, Italy; CNR-ISTI, Pisa, Italy; Dipartimento di Ingegneria Industriale, Università degli Studi di Firenze, Firenze, Italy; Namur Center for Complex Systems (naXys), University of Namur, Namur,Belgium
Intrinsic noise in objective function and derivatives evaluations may cause premature termination of optimization algorithms. Evaluation complexity bounds taking this situation into account are presented in the framework of a deterministic trust-region method. The results show that the presence of intrinsic noise may dominate these bounds, in contrast with what is known for methods in which the inexactness in function and derivatives' evaluations is fully controllable. Moreover, the new analysis provides estimates of the optimality level achievable, should noise cause early termination. Numerical experiments are reported that support the theory. The analysis finally sheds some light on the impact of inexact computer arithmetic on evaluation complexity.
Journal of optimization theory and applications
Trust-region, Noise, Evaluation complexity, Deterministic
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 476984
Year: 2023
Type: Articolo in rivista
Creation: 2023-01-26 14:58:23.000
Last update: 2023-02-02 18:15:46.000
CNR authors
External links
OAI-PMH: Dublin Core
OAI-PMH: Mods
OAI-PMH: RDF
DOI: 10.1007/s10957-022-02153-5
URL: https://link.springer.com/article/10.1007/s10957-022-02153-5
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:476984
DOI: 10.1007/s10957-022-02153-5
Scopus: 2-s2.0-85145939534
ISI Web of Science (WOS): 000911264400002