Hybrid nonmonotone spectral gradient method for the unconstrained minimization problem

Hybrid nonmonotone spectral gradient method for the unconstrained minimization problem Nonmonotone spectral gradient (NSG) techniques are considered for unconstrained optimization of differentiable functions. They combine a nonmonotone step length strategy, that is based on the Grippo–Lampariello–Lucidi nonmonotone line search, with the spectral gradient choice of steplength. In this paper, we present a hybrid nonmonotone spectral gradient method. In each iteration after finding an acceptable point by NSG method, we employ an extrapolation step to find a even better point by using particle swarm optimization. Through specific assumptions, we prove the global convergence of our proposed algorithm http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Computational and Applied Mathematics Springer Journals

Hybrid nonmonotone spectral gradient method for the unconstrained minimization problem

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Publisher
Springer International Publishing
Copyright
Copyright © 2016 by SBMAC - Sociedade Brasileira de Matemática Aplicada e Computacional
Subject
Mathematics; Applications of Mathematics; Computational Mathematics and Numerical Analysis; Mathematical Applications in the Physical Sciences; Mathematical Applications in Computer Science
ISSN
0101-8205
eISSN
1807-0302
D.O.I.
10.1007/s40314-016-0308-x
Publisher site
See Article on Publisher Site

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