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Scaling on diagonal quasi-Newton update for large-scale unconstrained optimization. (English) Zbl 1246.65092

The authors consider large-scale unconstrained optimization problems of the form \(\min_{x\in\mathbb{R}^n}\,f(x)\) and give a class of quasi-Newton methods that use some diagonal matrices to approximate the Hessian. Numerical results are given.

MSC:

65K05 Numerical mathematical programming methods
90C06 Large-scale problems in mathematical programming
90C30 Nonlinear programming
90C53 Methods of quasi-Newton type

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minpack; CUTEr; CUTE
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