Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
In the paper, we present algorithms for minimization of d.c. functions (difference of two convex functions) on the whole space$$R^n$$. Many nonconvex optimization problems can be described using these functions. D.c. functions are used in various applications especially in optimization, but the problem to characterize them is not trivial, due to the fact that these functions are not differentiable and certainly are not convex. The class of these functions is contained in the class of quasidifferentiable functions. Proposed algorithms are based on known necessary optimality conditions and d.c. duality. Convergence to$$\inf $$ -stationary points is established under fairly general natural assumptions.
Original language | English |
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Title of host publication | Computational Science and Its Applications – ICCSA 2019 |
Subtitle of host publication | 19th International Conference, Saint Petersburg, Russia, July 1–4, 2019, Proceedings, Part IV |
Editors | Sanjay Misra, et al. |
Publisher | Springer Nature |
Pages | 667–677 |
ISBN (Print) | 9783030243043 |
DOIs | |
State | Published - 2019 |
Event | 19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation Duration: 1 Jul 2019 → 4 Jul 2019 Conference number: 19 |
Name | LNCS |
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Volume | 11622 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference | 19th International Conference on Computational Science and Its Applications, ICCSA 2019 |
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Abbreviated title | ICCSA 2019 |
Country/Territory | Russian Federation |
City | Saint Petersburg |
Period | 1/07/19 → 4/07/19 |
ID: 43545567