Work

Enhancements Self-Scaling Quasi-Newton for Unconstrained Optimization

Year: 2024

Type: article

Abstract: A self-scaling for the quasi-Newton tecnique is derive by using a second_order Taylor's expansion to achieve optimal computational performance. Following this, new updating formulas for the quasi-Newton method are introduced based on the newly derived self-scaling equation. The numerical results confirm this derivation and suggest that the new method could potentially rival the BFGS method in terms of performance.

Source: Advances in Nonlinear Variational Inequalities

DOI: 10.52783/anvi.v27.974

Author: Basim A. Hassan

Institution: University of Mosul

Language: English

Topic: Advanced Optimization Algorithms Research

Subfield: Numerical Analysis

Field: Mathematics

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W4404422068

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