Theoretical and practical convergence of a self-adaptive penalty algorithm for constrained global optimization
This paper proposes a self-adaptive penalty function and presents a penalty-based algorithm for solving nonsmooth and nonconvex constrained optimization problems. We prove that the general constrained optimization problem is equivalent to a bound constrained problem in the sense that they have the s...
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| Other Authors: | , , |
| Format: | article |
| Language: | eng |
| Published: |
2017
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| Subjects: | |
| Online Access: | http://hdl.handle.net/1822/49143 |
| Country: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/49143 |