Skip to main content
Log in

Self-adaptive Forward–Backward Contraction-type Methods for Generalized Split Feasibility Problems

  • Published:
Mediterranean Journal of Mathematics Aims and scope Submit manuscript

Abstract

Based on the recent important results of Takahashi–Xu–Yao [Set-Valued and Variational Analysis 23(2015), 205–221] and other related results on split feasibility problems, we study a certain class of generalized split feasibility problems which includes many other split-type problems. We propose some new self-adaptive forward–backward contraction-type methods and prove that they converge strongly to a minimum-norm solution of the generalized split feasibility problems in real Hilbert spaces. As a by-product, we obtain self-adaptive methods for solving other classes of generalized split feasibility problems in real Hilbert spaces. Finally, we apply our results to solve an optimal control problem and an image restoration problem through numerical implementations, and compare our methods with related strongly convergent methods in the literature.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  1. Anh, P.K., Duong, V.T., Dung, V.T.: A strongly convergent Mann-type inertial algorithm for solving split variational inclusion problems. Optim. Eng. 22, 159–185 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  2. Beck, A., Teboulle, M.: A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM J. Imaging Sci. 2(1), 183–202 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  3. Butcher, J.C.: Numerical Methods for Ordinary Differential Equations. Wiley, New York (2003)

    Book  MATH  Google Scholar 

  4. Byrne, C.: A unified treatment for some iterative algorithms in signal processing and image reconstruction. Inverse Probl. 20, 103–120 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  5. Byrne, C.: Iterative oblique projection onto convex sets and the split feasibility problem. Inverse Probl. 18, 441–453 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  6. Ceng, L.C., Ansari, Q.H., Yao, J.C.: Relaxed extragradient methods for finding minimum-norm solutions of the split feasibility problem. Nonlinear Anal. 75, 2116–2125 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  7. Censor, Y., Bortfeld, T., Martin, B., Trofimov, A.: A unified approach for inversion problems in intensity modulated radiation therapy. Phys. Med. Biol. 51, 2353–2365 (2006)

    Article  Google Scholar 

  8. Censor, Y., Elfving, T.: A multiprojection algorithm using Bregman projections in product space. Numer. Algorithms 8, 221–239 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  9. Censor, Y., Gibali, A., Reich, S.: The Split Variational Inequality Problem (2010), arXiv:1009.3780v1

  10. Censor, Y., Gibali, A., Reich, S.: Algorithms for the split variational inequality problem. Numer. Algorithms 59, 301–323 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  11. Cegielski, A., Reich, S., Zalas, R.: Weak, strong and linear convergence of the CQ-method via the regularity of Landweber operators. Optimization 69, 605–636 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  12. Chidume, C.E., Nnakwe, M.O.: Iterative algorithms for split variational inequalities and generalized split feasibility problems with applications. J. Nonlinear Var. Anal. 3, 127–140 (2019)

    MATH  Google Scholar 

  13. Cholamjiak, W., Cholamjiak, P., Suantai, S.: An inertial forward-backward splitting method for solving inclusion problems in Hilbert spaces. J. Fixed Point Theory Appl. 20, Article number: 42 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  14. Combettes, P.L., Wajs, V.: Signal recovery by proximal forward-backward splitting. SIAM Multiscale Model Simul. 4, 1168–1200 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Dong, Q.L., Jiang, D., Cholamjiak, P., Shehu, Y.: A strong convergence result involving an inertial forward-backward algorithm for monotone inclusions. J. Fixed Point Theory Appl. 19, 3097–3118 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  16. Gibali, A.: A new Split Inverse Problem and application to least intensity feasible solutions. Pure Appl. Funct. Anal. 2, 243–258 (2017)

    MathSciNet  MATH  Google Scholar 

  17. Gibali, A., Mai, D.T., Vinh, N.T.: A new relaxed CQ algorithm for solving split feasibility problems in Hilbert spaces and its applications. J. Ind. Manag. Optim. 15, 963–984 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  18. He, S., Wu, T., Cho, Y.J., Rassias, T.M.: Optimal parameter selections for a general Halpern iteration. Numer. Algorithms 82, 1171–1188 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  19. He, S., Yang, C.: Solving the variational inequality problem defined on intersection of finite level sets. Abstr. Appl Anal. 1–8, Article ID 942315 (2013)

  20. Ibrahim, A.H., Kimiaei, M., Kumam, P.: A new black box method for monotone nonlinear equations. Optimization (2021). https://doi.org/10.1080/02331934.2021.2002326

    Article  Google Scholar 

  21. Ibrahim, A.H., Kumam, P., Kumam, P.: A family of derivative-free conjugate gradient methods for constrained nonlinear equations and image restoration. IEEE Access 8, 162714–162729 (2020)

    Article  Google Scholar 

  22. Izuchukwu, C., Mebawondu, A.A., Mewomo, O.T.: A new method for solving split variational inequality problem without co-coerciveness. J. Fixed Point Theory Appl. 22, Article number: 98 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  23. Izuchukwu, C., Ugwunnadi, G.C., Mewomo, O.T., Khan, A.R., Abbas, M.: Proximal-type algorithms for split minimization problem in p-uniformly convex metric spaces. Numer. Algorithms 82(3), 909–935 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  24. Izuchukwu, C., Okeke, C.C., Isiogugu, F.O.: A viscosity iterative technique for split variational inclusion and fixed point problems between a Hilbert space and a Banach space. J. Fixed Point Theory Appl. 20, Article number: 157 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  25. Kazmi, K.R., Ali, R., Furkan, M.: Hybrid iterative method for split monotone variational inclusion problem and hierarchical fixed point problem for a finite family of nonexpansive mappings. Numer. Algorithms 79, 499–527 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  26. Khan, S.A., Suantai, S., Cholamjiak, W.: Shrinking projection methods involving inertial forward-backward splitting methods for inclusion problems. RACSAM 113, 645–656 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  27. Khoroshilova, E.V.: Extragradient-type method for optimal control problem with linear constraints and convex objective function. Optim. Lett. 7, 1193–1214 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  28. Lemaire, B.: Which fixed point does the iteration method select? In: Gritzmann, P., Horst, R., Sachs, E., Tichatschke, R. (eds.) Recent Advances in Optimization. Lecture Notes in Economics and Mathematical Systems. Springer, Berlin (1997)

    Google Scholar 

  29. Liu, L.S.: Ishikawa and Mann iteration process with errors for nonlinear strongly accretive mappings in Banach spaces. J. Math. Anal. Appl. 194, 114–125 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  30. Masad, E., Reich, S.: A note on the multiple-set split convex feasibility problem in Hilbert space. J. Nonlinear Convex Anal. 8, 367–371 (2007)

    MathSciNet  MATH  Google Scholar 

  31. Moudafi, A.: Split monotone variational inclusions. J. Optim. Theory Appl. 150, 275–283 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  32. Ogbuisi, F.U., Izuchukwu, C.: Approximating a zero of sum of two monotone operators which solves a fixed point problem in reflexive Banach spaces. Numer. Funct. Anal. Optim. 42(3), 322–343 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  33. Ogwo, G.N., Izuchukwu, C., Mewomo, O.T.: Inertial methods for finding minimum-norm solutions of the split variational inequality problem beyond monotonicity. Numer. Algorithms 88, 1419–1456 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  34. Okeke, C.C., Izuchukwu, C.: A strong convergence theorem for monotone inclusion and minimization problems in complete CAT(0) spaces. Optim. Methods Softw. 34(6), 1168–1183 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  35. Pontryagin, L.S., Boltyanskii, V.G., Gamkrelidze, R.V., Mishchenko, E.F.: The Mathematical Theory of Optimal Processes. Wiley, New York (1962)

    MATH  Google Scholar 

  36. Reich, S.: Extension problems for accretive sets in Banach spaces. J. Functional Anal. 26, 378–395 (1977)

    Article  MathSciNet  MATH  Google Scholar 

  37. Reich, S., Tuyen, T.M.: A new algorithm for solving the split common null point problem in Hilbert spaces. Numer. Algorithms 83, 789–805 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  38. Rockafellar, R.T.: On the maximality of sums of nonlinear monotone operators. Trans. Am. Math. Soc. 149, 75–288 (1970)

    Article  MathSciNet  MATH  Google Scholar 

  39. Saejung, S., Yotkaew, P.: Approximation of zeros of inverse strongly monotone operators in Banach spaces. Nonlinear Anal. 75, 742–750 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  40. Seydenschwanz, M.: Convergence results for the discrete regularization of linear-quadratic control problems with bang-bang solutions. Comput. Optim. Appl. 629, 731–760 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  41. Suantai, S., Shehu, Y., Cholamjiak, P.: Nonlinear iterative methods for solving the split common null point problem in Banach spaces. Optim. Methods Softw. 34(4), 1–22 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  42. Süli, E., Mayers, D.F.: An Introduction to Numerical Analysis. Cambridge University Press, Cambridge (2003)

    Book  MATH  Google Scholar 

  43. Takahashi, W.: The split common null point problem in Banach spaces. Arch. Math. 104, 357–365 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  44. Takahashi, S., Takahashi, W.: The split common null point problem and the shrinking projection method in Banach spaces. Optimization 65, 281–287 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  45. Takahashi, W., Xu, H.K., Yao, J.C.: Iterative methods for generalized split feasibility problems in Hilbert spaces. Set-valued Var. Anal. 23(2), 205–221 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  46. Takahashi, W.: The split feasibility problem in Banach spaces. J. Nonlinear Convex Anal. 15, 1349–1355 (2014)

    MathSciNet  MATH  Google Scholar 

  47. Takahashi, W.: The split feasibility problem and the shrinking projection method in Banach spaces. J. Nonlinear Convex Anal. 16, 1449–1459 (2015)

    MathSciNet  MATH  Google Scholar 

  48. Tian, M., Jiang, B.-N.: Viscosity approximation methods for a class of generalized split feasibility problems with variational inequalities in Hilbert space. Numer. Funct. Anal. Optim. 40, 902–923 (2019)

    Article  MathSciNet  MATH  Google Scholar 

  49. Wang, Y., Xu, H.K.: Strong convergence for the proximal-gradient method. J. Nonlinear Convex Anal. 15, 581–593 (2014)

    MathSciNet  MATH  Google Scholar 

  50. Xu, H.K.: Iterative methods for split feasibility problem in infinite-dimensional Hilbert space. Inverse Probl. 26, 1–17 (2010)

    Article  MathSciNet  Google Scholar 

  51. Xu, H.K.: An iterative approach to quadratic optimization. J. Optim. Theory Appl. 116, 659–678 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  52. Yang, J., Liu, H.W.: Strong convergence result for solving monotone variational inequalities in Hilbert space. Numer. Algorithms 80, 741–752 (2019)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

The authors thank the reviewer for the time spent and efforts made to read through the manuscript and for his/her constructive comments, questions and suggestions, which have helped to improve the quality of the article.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chinedu Izuchukwu.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Izuchukwu, C., Jolaoso, L.O., Nnakwe, M.O. et al. Self-adaptive Forward–Backward Contraction-type Methods for Generalized Split Feasibility Problems. Mediterr. J. Math. 19, 204 (2022). https://doi.org/10.1007/s00009-022-02114-2

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00009-022-02114-2

Keywords

Mathematics Subject Classification

Navigation