Abstract
This paper proposes a hybrid method for solving systems of nonsmooth equations with box constraints, which combines the idea of Levenberg–Marquard-like method with the nonmonotone strategy and the smoothing approximation technique. Under mild assumptions, the proposed method is proven to possess global and local superlinear convergence. Preliminary numerical results are reported to show the efficiency of this proposed method in practical computation.
Similar content being viewed by others
References
Pang, J.S., Qi, L.Q.: Nonsmooth equations: motivation and algorithms. SIAM J. Optim. 3, 443–465 (1993)
Nocedal, J., Wright, S.J.: Numerical Optimization. Springer, New York (2006)
Ortega, J.M., Rheinboldt, W.C.: Iterative Solution of Nonlinear Equations in Several Variables. Academic Press, New York (1970)
Qi, L.Q.: A nonsmooth version of Newton’s methods. Math. Prog. 58, 353–368 (1993)
Qi, L.Q., Wei, Z.X., Yuan, G.L.: An active-set projected trust region algorithm with limited memory BFGS technique for box constrained nonsmooth equations. Optimization 62, 857–878 (2013)
Ou, Y.G.: A superlinearly convergent ODE-type trust region algorithm for nonsmooth nonlinear equations. J. Appl. Math. Comput. 22, 371–380 (2006)
Ling, C., Wang, G.F., He, H.J.: A new Levenberg–Marquardt type algorithm for solving nonsmooth constrained equations. Appl. Math. Comput. 229, 107–122 (2014)
Bian, W., Chen, X.J.: Neural network for nonsmooth, nonconvex constrained minimization via smooth approximation. IEEE Trans. Neural Netw. Learn. Syst. 25, 545–556 (2014)
Zhou, S., Yuan, G.L., Cui, Z., Duan, X.B., Wang, X.L.: An adaptive trust region algorithm for large-residual nonsmooth least squares problems. J. Ind. Manag. Optim. 14, 707–718 (2018)
Chen, X.J.: Smoothing methods for nonsmooth, nonconvex minimization. Math. Prog. 134, 71–99 (2012)
Yang, L., Chen, Y.P., Tong, X.J., Deng, C.L.: A new smoothing Newton method for solving constrained nonlinear equations. Appl. Math. Comput. 217, 9855–9863 (2011)
Grippo, L., Lamparillo, F., Lucidi, S.: A nonmonotone line search technique for Newton’s method. SIAM J. Numer. Anal. 23, 707–716 (1986)
Zhang, H.C., Hager, W.W.: A nonmonotone line search technique and its application to unconstrained optimization. SIAM J. Optim. 14, 1043–1056 (2004)
Gu, N.Z., Mo, J.T.: Incorporating nonmonotone strategies into the trust region method for unconstrained optimization. Comput. Math. Appl. 55, 2158–2172 (2008)
Ou, Y.G., Zhou, X.: A modified scaled memoryless BFGS preconditioned conjugate gradient algorithm for nonsmooth convex optimization. J. Ind. Manag. Optim. 14, 785–801 (2018)
Yu, Z.S.: On the global convergence of a Levenberg–Marquardt method for constrained nonlinear equation. J. Appl. Math. Comput. 16, 183–194 (2004)
Kanzow, C., Yamashita, N., Fukushima, M.: Levenberg–Marquardt methods for constrained nonlinear equations with strong local convergence properties. J. Comput. Appl. Math. 172, 375–397 (2004)
Yamashita, N., Fukushima, M.: On the rate of convergence of the Levenberg–Marquardt method. Computing 15, 237–249 (2001)
Powell, M.J.D.: A hybrid method for solving nonlinear equations. In: Rabinowitz, P. (ed.) Numerical Methods for Nonlinear Algebraic. Gordon and Breach Science, London (1970)
Fletcher, R., Xu, C.X.: Hybrid methods of nonlinear least squares. IMA J. Numer. Anal. 7, 371–389 (1987)
Nocedal, J., Yuan, Y.X.: Combing trust region and line search techniques. In: Yuan, Y.X. (ed.) Advances in Nonlinear Programming, pp. 153–175. Kluwer Academic, Dordrecht (1998)
Khan, S.H.: A Picard–Mann hybrid iterative process. Fixed Point Theory Appl. 2013, 69 (2013)
Ou, Y.G., Wang, G.S.: A hybrid ODE-based method for unconstrained optimization problems. Comput. Optim. Appl. 53, 249–270 (2012)
Petrović, M., Rakočević, V., Kontrec, N., Panić, S., Ilić, D.: Hybridization of accelerated gradient descent method. Numer. Algorithms 79, 769–786 (2018)
Petrovic, M.J., Stanimirovic, P.S., Kontrec, N., Mladenovic, J.: Hybrid modification of accelerated double direction method. Math. Prob. Eng. Volume 2018, Article ID 1523267 (2018)
Ou, Y.G.: A hybrid trust region algorithm for unconstrained optimization. Appl. Numer. Math. 61, 900–909 (2011)
Dolan, E.D., More, J.J.: Benchmarking optimization software with performance profiles. Math. Prog. Ser. A 91, 201–213 (2002)
Acknowledgements
The authors would like to thank the anonymous referees and the associate editor for their patience and valuable comments and suggestions that greatly improved this paper.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
This work is partially supported by NNSF of China (Nos. 11961018, 11261015) and NSF of Hainan Province (No. 2016CXTD004)
Rights and permissions
About this article
Cite this article
Ou, Y., Lin, H. A hybrid method for solving systems of nonsmooth equations with box constraints. Optim Lett 14, 2355–2377 (2020). https://doi.org/10.1007/s11590-020-01558-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11590-020-01558-3