An ADMM-based SQP method for separably smooth nonconvex optimization
Abstract This work is about a splitting approach for solving separably smooth nonconvex linearly constrained optimization problems. Based on the ideas from two classical methods, namely the sequential quadratic programming (SQP) and the alternating direction method of multipliers (ADMM), we propose...
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| Principais autores: | , |
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| Format: | Artigo |
| Jezik: | Inglês |
| Izdano: |
SpringerOpen
2020-03-01
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| Serija: | Journal of Inequalities and Applications |
| Teme: | |
| Online dostop: | http://link.springer.com/article/10.1186/s13660-020-02347-3 |
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