An augmented subgradient method for minimizing nonsmooth DC functions

Autor:	Sona Taheri, Adil M. Bagirov, N. Hoseini Monjezi
Rok vydání:	2021
Předmět:	Computational Mathematics Sequence Mathematical optimization Control and Optimization Line search Optimization problem Applied Mathematics Regular polygon Point (geometry) Subgradient method Critical point (mathematics) DC bias Mathematics
Zdroj:	Computational Optimization and Applications. 80:411-438
ISSN:	1573-2894 0926-6003
DOI:	10.1007/s10589-021-00304-4
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::4a331a7bef073c89da5fc3bf90d8cf1c https://doi.org/10.1007/s10589-021-00304-4 Zobrazit plný text záznamu Plný text ve formátu PDF