Genetic Algorithm-Based Shape Parameter Tuning for Radial Basis Function Interpolation
Abstract In this study, we address the non-trivial problem of determining the optimal shape parameter in radial basis function interpolation. We propose the use of a genetic algorithm, an optimization technique inspired by evolutionary selection, to identify this parameter. Numerical experiments are presented to evaluate the effectiveness of this approach, with direct comparisons to the leave-one-out cross-validation method, thereby highlighting its computational efficiency.
Authors
- Alessandra De Rossi (ORCID: https://orcid.org/0000-0003-1285-3820)
- Roberto Cavoretto (ORCID: https://orcid.org/0000-0001-6076-4115)
- Domenico Mezzanotte (ORCID: https://orcid.org/0000-0001-5154-6538)
- Sandro Lancellotti (ORCID: https://orcid.org/0000-0003-4253-3561)
Institutions
- Collegio Carlo Alberto (IT)
- University of Basilicata (IT)
- Istituto per le Applicazioni del Calcolo Mauro Picone (IT)
- University of Turin (IT)
Publication Details
- Journal
- Operations Research Forum
- Published
- 2026-02-16
- DOI
- https://doi.org/10.1007/s43069-026-00610-9
- Primary Topic
- Numerical methods in engineering
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Fondazione CRT
- Istituto Nazionale di Alta Matematica "Francesco Severi"
- European Commission
- Università degli Studi della Basilicata
- Gruppo Nazionale per il Calcolo Scientifico