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On descent-projection method for solving the split feasibility problems

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Abstract

Let Ω and C be nonempty, closed and convex sets in R n and R m respectively and A be an \({m \times n}\) real matrix. The split feasibility problem is to find \({u \in \Omega}\) with \({Au \in C.}\) Many problems arising in the image reconstruction can be formulated in this form. In this paper, we propose a descent-projection method for solving the split feasibility problems. The method generates the new iterate by searching the optimal step size along the descent direction. Under certain conditions, the global convergence of the proposed method is proved. In order to demonstrate the efficiency of the proposed method, we provide some numerical results.

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References

  1. Aubin J.P., Cellina A.: Differential Inclusions: Set-Valued Maps and Viability Theory. Springer, Berlin (1984)

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  4. Censor Y., Herman G.T.: On some optimization techniques in image reconstruction from projections. Appl. Numer. Math. 3, 365–391 (1987)

    Article  Google Scholar 

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

    Article  Google Scholar 

  6. Chinchuluum A., Pardalos P.M., Enkhbat R., Tseveendorj I.: Optimization and Control Problems. Springer, Berlin (2010)

    Google Scholar 

  7. Facchinei F., Pang J.S.: Finite-Dimensional Variational Inequalities and Complementarity Problems. Springer, New York (2003)

    Google Scholar 

  8. Fukushima M.: A relaxed projection method for variational inequalities. Math. Program. 35, 58–70 (1986)

    Article  Google Scholar 

  9. He B.S., Liao L.Z.: Improvements of some projection methods for monotone nonlinear variational inequalities. J. Optim. Theory Appl. 112, 111–128 (2002)

    Article  Google Scholar 

  10. Noor M.A.: General variational inequalities. Appl. Math. Lett. 1, 119–121 (1988)

    Article  Google Scholar 

  11. Noor M.A.: Some developments in general variational inequalities. Appl. Math. Comput. 152, 199–277 (2004)

    Article  Google Scholar 

  12. Noor M.A.: Extended general variational inequalities. Appl. Math. Lett. 22, 182–185 (2009)

    Article  Google Scholar 

  13. Noor M.A., Noor K.I., Rassias Th.M.: Some aspects of variational inequalities. J. Comput. Appl. Math. 47, 285–312 (1993)

    Article  Google Scholar 

  14. Polyak B.T.: Minimization of unsmooth functionals. USSR Comput. Math. Math. Phys. 9, 14–29 (1969)

    Article  Google Scholar 

  15. Qu B., Xiu N.H.: A note on the CQ algorithm for the split feasibility problem. Inverse Probl. 21, 1655–1665 (2005)

    Article  Google Scholar 

  16. Qu B., Xiu N.H.: A new halfspace-relaxation projection method for the split feasibility problem. Linear Algebra Appl. 428, 1218–1229 (2008)

    Article  Google Scholar 

  17. Rockafellar R.T.: Convex Analysis. Princeton University Press, Princeton (1970)

    Google Scholar 

  18. Stampacchia G.: Formes bilineaires coercivites sur les ensembles convexes. C. R. Acad. Sci. Paris 258, 4413–4416 (1964)

    Google Scholar 

  19. Yang Q.Z.: The relaxed CQ algorithm solving the split feasibility problem. Inverse Probl. 20, 1261–1266 (2004)

    Article  Google Scholar 

  20. Yang Q.: On variable-step relaxed projection algorithm for variational inequalities. J. Math. Anal. Appl. 302, 166–179 (2005)

    Article  Google Scholar 

  21. Yu, X., Shahzad, N., Yao, Y.: Implicit and explicit algorithms for solving the split feasibility problems, Optimization Letters. doi:10.1007/s11590-011-0340-0

  22. Zarantonello E.H.: Projections on convex sets in Hilbert space and spectral theory. In: Zarantonello, E.H. (eds) Contributions to Nonlinear Functional Analysis., Academic Press, New York (1971)

    Google Scholar 

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Correspondence to Muhammad Aslam Noor.

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Bnouhachem, A., Noor, M.A., Khalfaoui, M. et al. On descent-projection method for solving the split feasibility problems. J Glob Optim 54, 627–639 (2012). https://doi.org/10.1007/s10898-011-9782-2

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