Supermemory gradient methods for monotone nonlinear equations with convex constraints

DOI10.1007/s40314-015-0228-1zbMath1359.90136OpenAlexW1984506280MaRDI QIDQ520272

Yuanwen Liu, Yi-gui Ou

Publication date: 3 April 2017

Published in: Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s40314-015-0228-1

zbMATH Keywords

global convergenceprojection methodmonotone equationssupermemory gradient method

Mathematics Subject Classification ID

Numerical mathematical programming methods (65K05) Nonlinear programming (90C30) Numerical computation of solutions to systems of equations (65H10)

Related Items (7)

A unified derivative-free projection method model for large-scale nonlinear equations with convex constraints ⋮ A derivative-free multivariate spectral projection algorithm for constrained nonlinear monotone equations ⋮ A framework for convex-constrained monotone nonlinear equations and its special cases ⋮ A new conjugate gradient projection method for convex constrained nonlinear equations ⋮ Unnamed Item ⋮ A diagonal PRP-type projection method for convex constrained nonlinear monotone equations ⋮ Unnamed Item

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