Abstract
This paper deals with the solving of variational inequality problem where the constrained set is given as the intersection of a number of fixed-point sets. To this end, we present an extrapolated sequential constraint method. At each iteration, the proposed method is updated based on the ideas of a hybrid conjugate gradient method used to accelerate the well-known hybrid steepest descent method, and an extrapolated cyclic cutter method for solving a common fixed-point problem. We prove strong convergence of the method under some suitable assumptions of step-size sequences. We finally show the numerical efficiency of the proposed method compared to some existing methods.
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References
Aoyama, K., Kohsaka, F.: Viscosity approximation process for a sequence of quasi-nonexpansive mappings. Fixed Point Theory Appl. 17. https://doi.org/10.1186/1687-1812-2014-17 (2014)
Bauschke, H.H., Combettes, P.L.: A weak-to-strong convergence principle for Fejér-monotone methods in Hilbert spaces. Math. Oper. Res. 26, 248–264 (2001)
Bauschke, H.H., Combettes, P.L.: Convex Analysis and Monotone Operator Theory in Hilbert Spaces (2nd ed.) CMS Books in Mathematics. Springer, New York (2017)
Bregman, L.M.: Finding the common point of convex sets by the method of successive projection. Dokl. Akad. Nauk SSSR 162(3), 487–490 (1965)
Cegielski, A.: Generalized relaxations of nonexpansive operators and convex feasibility problems. Contemp. Math. 513, 111–123 (2010)
Cegielski, A.: Iterative Methods for Fixed Point Problems in Hilbert Spaces. Lecture Notes in Mathematics 2057. Springer, Berlin (2012)
Cegielski, A.: Application of quasi-nonexpansive operators to an iterative method for variational inequality. SIAM. J. Optim. 25(4), 2165–2181 (2015)
Cegielski, A., Censor, Y.: Opial-type theorems and the common fixed point problem. In: Bauschke, H., Burachik, R., Combettes, P., Elser, V., Luke, D., Wolkowicz, H (eds.) Fixed-Point Algorithms for Inverse Problems in Science and Engineering. Springer Optimization and Its Applications, vol. 49. Springer, New York (2011)
Cegielski, A., Censor, Y.: Extrapolation and local acceleration of an iterative process for common fixed point problems. J. Math. Anal. Appl. 394, 809–818 (2012)
Cegielski, A., Nimana, N.: Extrapolated cyclic subgradient projection methods for the convex feasibility problems and their numerical behaviour. Optimization 68, 145–161 (2019)
Cegielski, A., Zalas, R.: Methods for variational inequality problem over the intersection of fixed point sets of quasi-nonexpansive operators. Numer. Funct. Anal. Optim. 34, 255–283 (2013)
Dai, Y.H., Yuan, Y.: A nonlinear conjugate gradient method with a strong global convergence property. SIAM J. Optim. 10, 177–182 (1999)
Facchinei, F., Pang, J. -S.: Finite-Dimensional Variational Inequalities and Complementarity Problems, vol. I. Springer, New York (2003)
Fletcher, R., Reeves, C.M.: Function minimization by conjugate gradients. Comput. J. 7, 149–154 (1964)
Gibali, A., Reich, S., Zalas, R.: Outer approximation methods for solving variational inequalities in Hilbert space. Optimization 66, 417–437 (2017)
Gilbert, J.C., Nocedal, J.: Global convergence properties of conjugate gradient methods for optimization. SIAM J. Optim. 2, 21–42 (1992)
Goldstein, A.A.: Convex programming in Hilbert space. Bull. Am. Math. Soc. 70, 709–710 (1964)
Iiduka, H.: Three-term conjugate gradient method for the convex optimization problem over the fixed point set of a nonexpansive mapping. Appl. Math. Comput. 217, 6315–6327 (2011)
Iiduka, H.: Fixed point optimization algorithms for distributed optimization in networked systems. SIAM J. Optim. 23, 1–26 (2013)
Iiduka, H.: Convex optimization over fixed point sets of quasi-nonexpansive and nonexpansive mappings in utility-based bandwidth allocation problems with operational constraints. J. Comput. Appl. Math. 282, 225–236 (2015)
Iiduka, H.: Acceleration method for convex optimization over the fixed point set of a nonexpansive mapping. Math. Program. 149, 131–165 (2015)
Iiduka, H.: Distributed optimization for network resource allocation with nonsmooth utility functions. IEEE Trans. Control. Netw. Syst. 6, 1354–1365 (2019)
Iiduka, H.: Stochastic fixed point optimization algorithm for classifier ensemble. IEEE Trans Cybern. 50, 4370–4380 (2020)
Iiduka, H., Hishinuma, K.: Acceleration method combining broadcast and incremental distributed optimization algorithms. SIAM J. Optim. 24, 840–1863 (2014)
Iiduka, H., Yamada, I.: A use of conjugate gradient direction for the convex optimization problem over the fixed point set of a nonexpansive mapping. SIAM J. Optim. 19, 1881–1893 (2009)
Kaczmarz, S.: Angenäherte Auflösung von Systemen linearer Gleichungen. Bull. Int. A35, 355–357 (1937). English translation: Kaczmarz, S.: Approximate solution of systems of linear equations. Int. J. Contr. 57, 1269–1271 (1993)
Liu, C.: An acceleration scheme for row projection methods. J. Comput. Appl. 57, 363–391 (1995)
Maingé, P.E.: Strong convergence of projected subgradient methods for nonsmooth and nonstrictly convex minimization. Set-Valued Anal. 16, 899–912 (2008)
Nimana, N., Petrot, N., Prangprakhon, M.: A centralized three-term conjugate gradient method for variational inequality problem over the common fixed point constraints (submitted)
Nocedal, J., Wright, S.J.: Numerical Optimization. Springer, Springer Series in Operations Research and Financial Engineering, Berlin (1999)
Opial, Z.: Weak convergence of the sequence of successive approximations for nonexpansive mappings. Bull. Am. Math. Soc. 73, 591–597 (1967)
Prangprakhon, M., Nimana, N., Petrot, N.: A sequential constraint method for solving variational inequality over the intersection of fixed point sets. Thai J. Math. 18(3), 1105–1123 (2020)
Xu, H.K.: Iterative algorithm for nonlinear operators. J. London Math. Soc. 66, 240–256 (2002)
Yamada, I.: The hybrid steepest descent method for the variational inequality problem over the intersection of fixed point sets of nonexpansive mappings. In: Butnariu, D., Censor, Y., Reich, S (eds.) Inherently Parallel Algorithms in Feasibility and Optimization and their Applications, pp. 473–504. Elsevier, Amsterdam (2001)
Zarantonello, E.H.: Projections on convex sets in Hilbert space and spectral theory. In: Zarantonello, E. H. (ed.) Contributions to Nonlinear Functional Analysis, pp. 237–424. Academic Press, New York (1971)
Zhang, L., Zhou, W., Li, D.H.: A descent modified polak-ribiere-polyak conjugate gradient method and its global convergence. IMA J. Numer. Anal. 26, 629–640 (2006)
Zhang, L., Zhou, W., Li, D.H.: Global convergence of a modified fletcher-reeves conjugate gradient method with Armijo-type line search. Numer. Math. 104, 561–572 (2006)
Zhang, L., Zhou, W., Li, D.H.: Some descent three-term conjugate gradient methods and their global convergence. Optim. Methods Softw. 22, 697–711 (2007)
Acknowledgements
The authors are thankful to the Editor and two anonymous referees for comments and remarks which improved the quality and presentation of the paper. Mootta Prangprakhon was partially supported by Science Achievement Scholarship of Thailand (SAST), and Faculty of Science, Khon Kaen University. Nimit Nimana was partially supported by Thailand Science Research and Innovation under the project IRN62W0007.
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Prangprakhon, M., Nimana, N. Extrapolated sequential constraint method for variational inequality over the intersection of fixed-point sets. Numer Algor 88, 1051–1075 (2021). https://doi.org/10.1007/s11075-021-01067-z
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DOI: https://doi.org/10.1007/s11075-021-01067-z