Skip to main content
Log in

A projection algorithm for pseudomonotone vector fields with convex constraints on Hadamard manifolds

  • Original Paper
  • Published:
Numerical Algorithms Aims and scope Submit manuscript

Abstract

In this paper, we propose an algorithm for finding a zero of a pseudomonotone vector field with a convex constraint on a Hadamard manifold. This new method is the combination of the hyperplane projection method with specially constructed search directions. The global convergence property of this algorithm is established under the assumptions that the constructed halfspace is closed and convex, the tangent vector field is continuous, and the solution set is nonempty. Numerical experiments show the efficiency of this new derivative-free iterative method.

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

Similar content being viewed by others

References

  1. Absil, P.-A., Mahony, R., Sepulchre, R.: Optimization Algorithms on Matrix Manifolds. Princeton University Press, Princeton (2008)

    Book  MATH  Google Scholar 

  2. Adler, R.L., Dedieu, J.-P., Margulies, J.Y., Martens, M., Shub, M.: Newton’s method on Riemannian manifolds and a geometric model for the human spine. IMA J. Numer. Anal. 22, 359–390 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  3. Ansari, Q.H., Islam, M., Yao, J.C.: Nonsmooth convexity and monotonicity in terms of a bifunction on Riemannian manifolds. J. Nonlinear Convex Anal. 18, 743–762 (2017)

    MathSciNet  MATH  Google Scholar 

  4. Ansari, Q.H., Babu, F., Li, X.B.: Variational inclusion problems in Hadamard manifolds. J. Nonlinear Convex Anal. 19, 219–237 (2018)

    MathSciNet  MATH  Google Scholar 

  5. Ansari, Q.H., Babu, F.: Existence and boundedness of solutions to inclusion problems for maximal monotone vector fields in Hadamard manifolds. Optim. Lett. 14, 711–727 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  6. Batista, E.E.A., Bento, G.C., Ferreira, O.P.: An extragradient-type algorithm for variational inequality on Hadamard manifolds. ESAIM Control Optim. Calc. Var. https://doi.org/10.1051/cocv/2019040 (2019)

  7. Bento, G.C., Ferreira, O.P., Melo, J.G.: Iteration-complexity of gradient, subgradient and proximal point methods on Riemannian manifolds. J. Optim. Theory Appl. 173, 548–562 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  8. Cheng, W.Y.: A PRP type method for systems of monotone equations. Math. Comput. Model. 50, 15–20 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  9. Da Cruz Neto, J.X., Ferreira, O.P., Lucambio Pérez, L.R.: Monotone point-to-set vector fields. Balk. J. Geom. Appl. 5, 69–79 (2000)

    MathSciNet  MATH  Google Scholar 

  10. Da Cruz Neto, J.X., Ferreira, O.P., Lucambio Pérez, L.R.: Contributions to the study of monotone vector fields. Acta. Math. Hung. 94, 307–320 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  11. Da Cruz Neto, J.X., Ferreira, O.P., Lucambio Pérez, L.R., Németh, S.Z.: Convex and monotone-transformable mathematical programming problems and a proximal-like point method. J. Global Optim. 35, 53–69 (2006)

    Article  MathSciNet  MATH  Google Scholar 

  12. Dedieu, J.P., Priouret, P., Malajovich, G.: Newton’s method on Riemannian manifolds: Covariant alpha theory. IMA J. Numer. Anal. 23, 395–419 (2003)

    Article  MathSciNet  MATH  Google Scholar 

  13. Ferreira, O.P., Oliveira, P.R.: Proximal point algorithm on Riemannian manifolds. Optimization 51, 257–270 (2002)

    Article  MathSciNet  MATH  Google Scholar 

  14. Ferreira, O.P., Pérez, L.R.L., Németh, S.Z.: Singularities of monotone vector fields and an extragradient-type algorithm. J. Glob. Optim. 31, 133–151 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  15. Li, C., López, G., Martín-Márquez, M.: Monotone vector fields and the proximal point algorithm on Hadamard manifolds. J. Lond. Math. Soc. 79, 663–683 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  16. Li, C., López, G., Martín-Márquez, M.: Resolvents of set-valued monotone vector fields in Hadamard manifolds. Set Valued Anal. 19, 361–383 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  17. Li, C., Wang, J.H.: Convergence of the Newton method and uniqueness of zeros of vector fields on Riemannian manifolds. Sci. China Ser. A. 48, 1465–1478 (2005)

    Article  MathSciNet  MATH  Google Scholar 

  18. Li, C., Yao, J.C.: Variational inequalities for set-valued vector fields on Riemannian manifolds: convexity of the solution set and the proximal point algorithm. SIAM J. Control Optim. 50, 2486–2514 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  19. Li, Q.N., Li, D.H.: A class of derivative-free methods for large-scale nonlinear monotone equations. IMA J. Numer. Anal. 31, 1625–1635 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  20. Li, S.L., Li, C., Liou, Y.C., Yao, J.C.: Existence of solutions for variational inequalities on Riemannian manifolds. Nonlinear Anal. 71, 5695–5706 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  21. Németh, S.Z.: Geodesic monotone vector fields. Lobachevskii J. Math. 5, 13–28 (1999)

    MathSciNet  MATH  Google Scholar 

  22. Souza, J.C.O., Oliveira, P.R.: A proximal point algorithm for DC fuctions on Hadamard manifolds. J. Glob. Optim. 63, 797–810 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  23. Tang, G.J., Huang, N.J.: Korpelevich’s method for variational inequality problems on Hadamard manifolds. J. Global Optim. 54, 493–509 (2012)

    Article  MathSciNet  MATH  Google Scholar 

  24. Tang, G.J., Huang, N.J.: An inexact proximal point algorithm for maximal monotone vector fields on Hadamard manifolds. Oper. Res. Lett. 41, 586–591 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  25. Tang, G.J., Wang, X., Liu, H.W.: Projection-type method for variational inequalities on Hadamard manifolds and verification of solution existence. Optimization 64, 1081–1096 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  26. Wang, C.W., Wang, Y.J., Xu, C.L.: A projection method for a system of nonlinear monotone equations with convex constraints. Math. Methods Oper. Res. 66, 33–46 (2007)

    Article  MathSciNet  MATH  Google Scholar 

  27. Wang, J.H., Li, C., Lopez, G., Yao, J.-C.: Convergence analysis of inexact proximal point algorithms on Hadamard manifolds. J Global Optim. 61, 553–573 (2015)

    Article  MathSciNet  MATH  Google Scholar 

  28. Wang, J.H., Li, C., Lopez, G., Yao, J.-C.: Proximal point algorithms on Hadamard manifolds: linear convergence and finite termination. SIAM J. Optim. 26, 2696–2729 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  29. Xiao, Y.H., Zhu, H.: A conjugate gradient method to solve convex constrained monotone equations with applications in compressive sensing. J. Math. Anal. Appl. 405, 310–319 (2013)

    Article  MathSciNet  MATH  Google Scholar 

  30. Yao, T.T., Zhao, Z., Bai, Z.J., Jin, X.Q.: A Riemannian derivative-free polak-ribiére-polyak method for tangent vector field. Numer. Algorithms 86, 325–355 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  31. Yu, Z.S., Lin, J., Sun, J., Xiao, Y.H., Liu, L.Y., Li, Z.H.: Spectral gradient projection method for monotone nonlinear equations with convex constraints. Appl. Numer. Math. 59, 2416–2423 (2009)

    Article  MathSciNet  MATH  Google Scholar 

  32. Yuan, G.L., Meng, Z.H., Li, Y.: A modified Hestenes and Stiefel conjugate gradient algorithm for large-scale nonsmooth minimizations and nonlinear equations. J. Optim. Theory Appl. 168, 129–152 (2016)

    Article  MathSciNet  MATH  Google Scholar 

  33. Zhang, L., Zhou, W.J.: Spectral gradient projection method for solving nonlinear monotone equations. J. Comput. Appl. Math. 196, 478–484 (2006)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Acknowledgements

We are very grateful to the two anonymous referees for their valuable comments on the paper, which have considerably improved the paper.

Funding

The research of Zhi Zhao is supported by the Zhejiang Provincial Natural Science Foundation of China (No. LY21A010010) and the National Natural Science Foundation of China (No. 11601112). The research of Ya-Guan Qian is supported by National Key R&D Program of China (No. 2018YFB2100400). The research of Teng-Teng Yao is supported by the Zhejiang Provincial Natural Science Foundation of China (No. LY21A010004) and The National Natural Science Foundation of China (No. 11701514).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Teng-Teng Yao.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Data availability

Data sharing not applicable to this article as no data sets were generated or analyzed during the current study.

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 (e.g. a society or other partner) 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

Zhao, Z., Zeng, Q., Xu, YN. et al. A projection algorithm for pseudomonotone vector fields with convex constraints on Hadamard manifolds. Numer Algor 93, 1209–1223 (2023). https://doi.org/10.1007/s11075-022-01464-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11075-022-01464-y

Keywords

Mathematics Subject Classification (2010)

Navigation