| Autor: |
Cunha, F. G. M., da Cruz Neto, J.X., Oliveira, P. R. |
| Předmět: |
|
| Zdroj: |
Optimization; Jul2010, Vol. 59 Issue 5, p777-792, 16p, 9 Charts |
| Abstrakt: |
We apply the proximal point method with the ϕ-divergence given by [image omitted] for the minimization of quasiconvex functions subject to non-negativity constraints. We prove, without the assumption of the boundedness level to the objective function, that the sequence generated by our algorithm is well-defined and it converges to a stationary point when the regularization parameter λk satisfies [image omitted], for some [image omitted]. If, in addition, [image omitted], we then obtain the convergence to an optimal solution. We verify the effectiveness of the proximal algorithm via numerical experiments accomplished with randomly generated test problems. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
|
