TY - JOUR
ID - 24567
TI - Augmented Lagrangian Method for Finding Minimum Norm Solution to the Absolute Value Equation
JO - Iranian Journal of Numerical Analysis and Optimization
JA - IJNAO
LA - en
SN - 2423-6977
AU - Ketabchi, S.
AU - Moosaei, H.
AD - Department of Applied Mathematics, Faculty of Mathematical Sciences, University of Guilan, P.O. Box 1914, Rasht, Iran.
AD - Department of Mathematics, Faculty of Science, University of Bojnord, Bojnord, Iran.
Y1 - 2017
PY - 2017
VL - 7
IS - 2
SP - 57
EP - 64
KW - Absolute value equation
KW - Minimum norm solution
KW - Generalized Newton method
KW - Augmented Lagrangian method
DO - 10.22067/ijnao.v7i2.57912
N2 - In this paper, we give an algorithm to compute the minimum 1-norm solution to the absolute value equation (AVE). The augmented Lagrangian method is investigated for solving this problems . This approach leads to an unconstrained minimization problem with once differentiable convex objective function. We propose a quasi-Newton method for solving unconstrained optimization problem. Computational results show that convergence to high accuracy often occurs in just a few iterations.
UR - https://ijnao.um.ac.ir/article_24567.html
L1 - https://ijnao.um.ac.ir/article_24567_25c1b6aedf63ce96172f888d48396484.pdf
ER -