292. ɛ-subdifferential methods for global DC optimization
Invited abstract in session TB-4: Stochastic and Deterministic Global Optimization, stream Global optimization.
Tuesday, 10:30-12:30Room: B100/5013
Authors (first author is the speaker)
| 1. | Adil Bagirov
|
| The Centre for Smart Analytics, Institute of Innovation, Science and Sustainability, Federation University Australia |
Abstract
In this talk, we discuss methods for solving the difference of convex (DC) optimization problems subject to box constraints. These methods are based on the combination of local and global search methods where the local methods are used to find stationary points of the problem and the global methods are used to escape from these points. The escaping procedure is designed using ɛ-subdifferentials of DC components. Convergence of the proposed methods are discussed. We report results of numerical experiments using academic test problems and compare methods with the state of the-art global optimization solvers.
Keywords
- Global optimization
- Non-smooth optimization
- Computational mathematical optimization
Status: accepted
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