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On the contraction-proximal point algorithms with multi-parameters

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Abstract

In this paper we consider the contraction-proximal point algorithm: \({x_{n+1}=\alpha_nu+\lambda_nx_n+\gamma_nJ_{\beta_n}x_n,}\) where \({J_{\beta_n}}\) denotes the resolvent of a monotone operator A. Under the assumption that lim n  α n  = 0, ∑ n  α n  = ∞, lim inf n  β n  > 0, and lim inf n γ n  > 0, we prove the strong convergence of the iterates as well as its inexact version. As a result we improve and recover some recent results by Boikanyo and Morosanu.

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References

  1. Bauschke H.H., Combettes P.L.: A weak-to-strong convergence principle for Fejér-monotone methods in Hilbert spaces. Math. Oper. Res. 26, 248–264 (2001)

    Article  Google Scholar 

  2. Boikanyo O.A., Morosanu G.: A proximal point algorithm converging strongly for general errors. Optim. Lett. 4, 635–641 (2010)

    Article  Google Scholar 

  3. Boikanyo O.A., Morosanu G.: Four parameter proximal point algorithms. Nonlinear Anal. 74, 544–555 (2011)

    Article  Google Scholar 

  4. Boikanyo, O.A., Morosanu, G.: Inexact Halpern-type proximal point algorithm, J. Glob. Optim. (to appear)

  5. Goebel K., Kirk W.A.: Topics on Metric Fixed Point Theory. Cambridge University Press, Cambridge (1990)

    Book  Google Scholar 

  6. Güler O.: On the convergence of the proximal point algorithm for convex optimization. SIAM J. Control Optim. 29, 403–419 (1991)

    Article  Google Scholar 

  7. Kamimura S., Takahashi W.: Approximating solutions of maximal monotone operators in Hilbert spaces. J. Approx. Theory 106, 226–240 (2000)

    Article  Google Scholar 

  8. Lehdili N., Moudafi A.: Combining the proximal algorithm and Tikhonov method. Optimization 37, 239–252 (1996)

    Article  Google Scholar 

  9. Maingé P.E.: Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization. Set-Valued Anal. 16, 899–912 (2008)

    Article  Google Scholar 

  10. Marino G., Xu H.K.: Convergence of generalized proximal point algorithm. Comm. Pure Appl. Anal. 3, 791–808 (2004)

    Article  Google Scholar 

  11. Rockafellar R.T.: Monotone operators and the proximal point algorithm. SIAM J. Control Optim. 14, 877–898 (1976)

    Article  Google Scholar 

  12. Solodov M.V., Svaiter B.F.: Forcing strong convergence of proximal point iterations in a Hilbert space. Math. Program. Ser. A 87, 189–202 (2000)

    Google Scholar 

  13. Song Y., Yang C.: A note on a paper “A regularization method for the proximal point algorithm”. J. Global Optim. 43, 171–174 (2009)

    Article  Google Scholar 

  14. Wang F.: A note on the regularized proximal point algorithm. J. Glob. Optim. 50, 531–535 (2011)

    Article  Google Scholar 

  15. Xu H.K.: A regularization method for the proximal point algorithm. J. Glob. Optim. 36, 115–125 (2006)

    Article  Google Scholar 

  16. Xu H.K.: Iterative algorithms for nonlinear operators. J. Lond. Math. Soc. 66, 240–256 (2002)

    Article  Google Scholar 

  17. Yao Y., Noor M.A.: On convergence criteria of generalized proximal point algorithms. J. Comput. Appl. Math. 217, 46–55 (2008)

    Article  Google Scholar 

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Correspondence to Fenghui Wang.

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Wang, F., Cui, H. On the contraction-proximal point algorithms with multi-parameters. J Glob Optim 54, 485–491 (2012). https://doi.org/10.1007/s10898-011-9772-4

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  • DOI: https://doi.org/10.1007/s10898-011-9772-4

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