Nonconvex optimization, Nonsmooth optimization, Sharp augmented Lagrangian, Modified subgradient method, Inexact minimization, Bang-bang control,

A. Nedić

A.C. Floudas

A.J. Wood

B.T. Polyak

C. Yalçın Kaya

C.T. Kelley

C.Y. Kaya

C.Y. Wang

E. Mijangos

H.D. Sherali

J.C. Lagarias

J.C. Price

K. Kiwiel

K.I.M. McKinnon

M.S. Bazaraa

Musa Mammadov

N.Z. Shor

R.N. Gasimov

R.S. Burachik

R.T. Rockafellar

Regina S. Burachik

U. Brännlund

X. Tong

We propose and analyze an inexact version of the modified subgradient (MSG) algorithm, which we call the IMSG algorithm, for nonsmooth and nonconvex optimization over a compact set. We prove that under an approximate, i.e. inexact, minimization of the sharp augmented Lagrangian, the main convergence properties of the MSG algorithm are preserved for the IMSG algorithm. Inexact minimization may allow to solve problems with less computational effort. We illustrate this through test problems, including an optimal bang-bang control problem, under several different inexactness schemes. © 2008 Springer Science+Business Media, LLC.C

Burachik, Regina

Kaya, Yalcin

Mammadov, Musa

Federation ResearchOnline

Computational Optimization and Applications

An inexact modified subgradient algorithm for nonconvex optimization

Regina Burachik

C. Kaya

Research Papers in Economics

Crossref

Burachik, Regina S.

Kaya, C. Yalçın

Deakin Research Online

An inexact modified subgradient algorithm for nonconvex optimization

http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.216.4208

An inexact modified subgradient algorithm for nonconvex optimization

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Federation ResearchOnline

Research Papers in Economics

Crossref

Deakin Research Online