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A new diagonal quasi-Newton algorithm for unconstrained optimization problems
Applications of Mathematics, Tome 69 (2024) no. 4, pp. 501-512 Cet article a éte moissonné depuis la source Czech Digital Mathematics Library

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We present a new diagonal quasi-Newton method for solving unconstrained optimization problems based on the weak secant equation. To control the diagonal elements, the new method uses new criteria to generate the Hessian approximation. We establish the global convergence of the proposed method with the Armijo line search. Numerical results on a collection of standard test problems demonstrate the superiority of the proposed method over several existing diagonal methods.
We present a new diagonal quasi-Newton method for solving unconstrained optimization problems based on the weak secant equation. To control the diagonal elements, the new method uses new criteria to generate the Hessian approximation. We establish the global convergence of the proposed method with the Armijo line search. Numerical results on a collection of standard test problems demonstrate the superiority of the proposed method over several existing diagonal methods.
DOI : 10.21136/AM.2024.0045-24
Classification : 65K05, 90C30
Keywords: unconstrained optimization; diagonal quasi-Newton method; weak secant equation; global convergence 
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     title = {A new diagonal {quasi-Newton} algorithm for unconstrained optimization problems},
     journal = {Applications of Mathematics},
     pages = {501--512},
     year = {2024},
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Nosrati, Mahsa; Amini, Keyvan. A new diagonal quasi-Newton algorithm for unconstrained optimization problems. Applications of Mathematics, Tome 69 (2024) no. 4, pp. 501-512. doi: 10.21136/AM.2024.0045-24

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