Scaling Damped Limited-Memory Updates for Unconstrained Optimization

Fahimeh Biglari () and Farideh Mahmoodpur
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Fahimeh Biglari: Urmia University of Technology
Farideh Mahmoodpur: Urmia University of Technology

Journal of Optimization Theory and Applications, 2016, vol. 170, issue 1, No 11, 177-188

Abstract: Abstract This paper investigates scaling a modified limited-memory algorithm to solve unconstrained optimization problems. The basic idea was to combine the damped techniques for the limited-memory update and the technique of equilibrating the inverse Hessian matrix. Enhanced curvature information about the objective function is stored in the form of a diagonal matrix and plays the dual roles of providing an initial matrix and equilibrating for damped limited-memory iterations. Numerical experiments indicated that the new algorithm is very effective.

Keywords: Large-scale optimization; Nonlinear programming; Limited-memory quasi-Newton methods; Damped technique; Scaling technique; 90C06; 90C30 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10957-016-0940-z

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