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An augmented subgradient method for minimizing nonsmooth DC functions by A. M. Bagirov; N. Hoseini Monjezi; S. Taheri is a Computer Science article available to read on EtoBox.

What is An augmented subgradient method for minimizing nonsmooth DC functions about?

A method, called an augmented subgradient method, is developed to solve unconstrained nonsmooth difference of convex (DC) optimization problems. At each iteration of this method search directions are found by using several subgradients of the first DC component and one subgradient of the second DC component of the objective function. The developed method applies an Armijo-type line search procedure to find the next iteration point. It is proved that the sequence of points generated by the method converges to a critical point of the unconstrained DC optimization problem. The performance of the method is demonstrated using academic test problems with nonsmooth DC objective functions and its performance is compared with that of two general nonsmooth optimization solvers and five solvers specifically designed for unconstrained DC optimization. Computational results show that the developed method is efficient and robust for solving nonsmooth DC optimization problems.

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Author

A. M. Bagirov; N. Hoseini Monjezi; S. Taheri

Publisher

Springer Science and Business Media LLC

Published

2021

Language

EN

Field

Computer Science (Physical Sciences)