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Two algorithms for solving systems of inclusion problems

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Abstract

The goal of this paper is to present two algorithms for solving systems of inclusion problems, with all components of the systems being a sum of two maximal monotone operators. The algorithms are variants of the forward-backward splitting method and one being a hybrid with the alternating projection method. They consist of approximating the solution sets involved in the problem by separating half-spaces which is a well-studied strategy. The schemes contain two parts, the first one is an explicit Armijo-type search in the spirit of the extragradient-like methods for variational inequalities. The second part is the projection step, this being the main difference between the algorithms. While the first algorithm computes the projection onto the intersection of the separating half-spaces, the second chooses one component of the system and projects onto the separating half-space of this case. In the iterative process, the forward-backward operator is computed once per inclusion problem, representing a relevant computational saving if compared with similar algorithms in the literature. The convergence analysis of the proposed methods is given assuming monotonicity of all operators, without Lipschitz continuity assumption. We also present some numerical experiments.

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References

  1. Al-Homidan, S., Alshahrani, M., Ansari, Q.H.: System of nonsmooth variational inequalities with applications. Optimization 64(5), 1211–1218 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  2. Bauschke, H.H., Borwein, J.M.: On projection algorithms for solving convex feasibility problems. SIAM Rev. 38, 367–426 (1996)

    Article  MathSciNet  MATH  Google Scholar 

  3. Bauschke, H.H., Combettes, P.L.: Convex analysis and monotone operator theory in hilbert spaces. Springer (2011)

  4. Bello Cruz, J.Y., Díaz Millán, R.: A variant of forward-backward splitting method for the sum of two monotone operators with a new search strategy. Optimization 64(7), 1471–1486 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  5. Browder, F.E.: Convergence theorems for sequences of nonlinear operators in Banach spaces. Math. Z. 100, 201–225 (1967)

    Article  MathSciNet  MATH  Google Scholar 

  6. Censor, Y., Gibali, A., Reich, S.: A von Neumann alternating method for finding common solutions to variational inequalities. Nonlinear Analysis Series A: Theory, Methods and Applications 75, 4596–4603 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  7. Censor, Y., Gibali, A., Reich, S., Sabach, S.: Common solutions to variational inequalities. Set-Valued and Variational Analysis 20, 229–247 (2012)

    Article  MathSciNet  MATH  Google Scholar 

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

    Article  MathSciNet  MATH  Google Scholar 

  9. Combettes, P.L.: Fejér monotonicity in convex optimization. Encyclopedia of Optimization 1016–1024 (2009)

  10. Díaz Millán, R.: On several algorithms for variational inequality and inclusion problems. PhD thesis, Federal University of Goiás, Goiânia, GO. Institute of Mathematic and Statistic, IME-UFG (2015)

  11. Douglas, J., Rachford Jr., H.H.: On the numerical solution of heat conduction problems in two or three space variables. Trans. Amer. Math. Soc. 82, 421–439 (1956)

    Article  MathSciNet  MATH  Google Scholar 

  12. Eckstein, J.: Splitting methods for monotone operators, with applications to parallel optimization. PhD Thesis, Massachusetts Institute of Techonology, Cambridge, MA. Report LIDS-TH-1877, Laboratory for Information and Decision Systems, M.I.T (1989)

  13. Eslamian, M., Saejung, S., Vahidi, J.: Common solutions of a system of variational inequality problems. UPB Scientific Bulletin Series A: Applied Mathematics and Physics Seria A 77(1), 55–62 (2015)

    MathSciNet  MATH  Google Scholar 

  14. Harker, P.T., Pang, J.S.: A damped-newton method for the linear complementarity problem. Lect. Appl. Math. 26, 265–284 (1990)

    MathSciNet  MATH  Google Scholar 

  15. Iusem, A.N., Svaiter, B.F., Teboulle, M.: Entropy-like proximal methods in convex programming. Math. Oper. Res. 19, 790–814 (1994)

    Article  MathSciNet  MATH  Google Scholar 

  16. Kopecká, E., Reich, S.: Another note on the von Neumann alternating projections algorithm. Journal of Nonlinear and Convex Analysis 11(3), 455–460 (2010)

    MathSciNet  MATH  Google Scholar 

  17. Kopecká, E., Reich, S.: A note on the von Neumann alternating projections algorithm. Journal of Nonlinear Convex Analysis 5, 379–386 (2004)

    MathSciNet  MATH  Google Scholar 

  18. Konnov, I.V.: On systems of variational inequalities. Russian Mathematics 41(12), 79–88 (1997)

    MathSciNet  Google Scholar 

  19. Konnov, I.V.: Splitting-type method for systems of variational inequalities. Comput. Oper. Res. 33, 520–534 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  20. Minty, G.: On the maximal domain of a “monotone” function. Mich. Math. J. 8, 135–137 (1961)

    Article  MathSciNet  MATH  Google Scholar 

  21. Minty, G.: Monotone (nonlinear) operators in Hilbert Space. Duke Mathematical Journal 29, 341–346 (1962)

    Article  MathSciNet  MATH  Google Scholar 

  22. Rosasco, L., Villa, S., Vu, B.C.: Stochastic forward-backward splitting for monotone inclusions. J. Optim. Theory Appl. 169(2), 388–406 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  23. Semenov, V.V.: Hybrid splitting methods for the system of operator inclusions with monotone operators. Cybern. Syst. Anal. 50, 741–749 (2014)

    Article  MathSciNet  MATH  Google Scholar 

  24. Villa, S., Salzo, S., Baldassarre, L., Verri, A.: Accelerated and inexact forward-backward algorithms. SIAM J. Optim. 23(3), 1607–1633 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  25. Tseng, P.: A modified forward-backward splitting method for maximal monotone mappings. SIAM J. Control. Optim. 38, 431–446 (2000)

    Article  MathSciNet  MATH  Google Scholar 

  26. Van Hieu, D., Anh, P.K., Muu, L.D.: Modified hybrid projection methods for finding common solutions to variational inequality problems. Comput. Optim. Appl. (2016)

  27. Zarantonello, E.H.: Projections on convex sets in Hilbert space and spectral theory. In: Zarantonello, E (ed.) Contributions to Nonlinear Functional Analysis, pp 237–424. Academic Press, New York (1971)

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Acknowledgments

The author was partially supported by CNPq grant 200427/2015-6. This work was concluded while the author was visiting the School of Information Technology and Mathematical Sciences at the University of South Australia. The author would like to thank the great hospitality received during his visit, particularly to Regina S. Burachik and C. Yalçin Kaya. The author would like to express his gratitude to two anonymous referees for their valuable comments and suggestions that are very helpful to improve this paper.

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Díaz Millán, R. Two algorithms for solving systems of inclusion problems. Numer Algor 78, 1111–1127 (2018). https://doi.org/10.1007/s11075-017-0415-9

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  • DOI: https://doi.org/10.1007/s11075-017-0415-9

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