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...
| Autor principal: | |
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| Outros Autores: | , , |
| Formato: | article |
| Idioma: | eng |
| Publicado em: |
2017
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| Assuntos: | |
| Texto completo: | http://hdl.handle.net/1822/49143 |
| País: | Portugal |
| Oai: | oai:repositorium.sdum.uminho.pt:1822/49143 |