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February 19, 2026Operations Research Forum0 citationsOpen Access

Genetic Algorithm-Based Shape Parameter Tuning for Radial Basis Function Interpolation

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RCRoberto CavorettoARAlessandra De RossiSLSandro Lancellotti

Key Points

  • The aim is to determine the optimal shape parameter for radial basis function interpolation using a genetic algorithm.
  • Utilized a genetic algorithm inspired by evolutionary selection for optimization.
  • Conducted numerical experiments to validate the approach.
  • Compared outcomes with standard leave-one-out cross-validation method.
  • The genetic algorithm successfully identified optimal shape parameters.
  • Demonstrated improved computational efficiency compared to traditional methods.

Abstract

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.

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Cite This Study

Cavoretto et al. (2026) studied this question.

synapsesocial.com/papers/6996a7ffecb39a600b3ee4ffhttps://doi.org/10.1007/s43069-026-00610-9
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