Abstract
For most projection methods, the operator of a variational inequality problem is assumed to be monotone (or pseudomonotone) and Lipschitz continuous. In this paper, we present a projection-like method to solve quasimonotone variational inequality problems without Lipschitz continuity. Under some mild assumptions, we prove that the sequence generated by the proposed algorithm converges to a solution. Numerical experiments are provided to show the effectiveness of the method.
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References
Korpelevich, G.M.: The extragradient method for finding saddle points and other problems. Ekonomika i Mat Metody. 12, 747–756 (1976)
Censor, Y., Gibali, A., Reich, S.: The subgradient extragradient method for solving variational inequalities in Hilbert space. J. Optim. Theory Appl. 148, 318–335 (2011)
Censor, Y., Gibali, A., Reich, S.: Strong convergence of subgradient extragradient methods for the variational inequality problems in Hilbert space. Optim. 26, 827–845 (2011)
Censor, Y., Gibali, A., Reich, S.: Extensions of Korpelevich’s extragradient method for the variational inequality problem in Euclidean space. Optim. 61, 1119–1132 (2012)
Gibali, A.: A new Bregman projection method for solving variational inequalities in Hilbert spaces. Pure Appl. Funct. Anal. 3, 403–415 (2018)
Hieu, D.V., Thong, D.V.: New extragradient-like algorithms for strongly pseudomonotone variational inequalities. J. Glob. Optim. 70, 385–399 (2018)
Malitsky, Y.V., Semenov, V.V.: An extragradient algorithm for monotone variational inequalities. Cybern. Syst. Anal. 50, 271–277 (2014)
Rockfellar, R.T.: Monotone operators and proximal point algorithm. SIAM J. Control. Optim. 14, 877–898 (1976)
He, Y.R.: A new double projection algorithm for variational inequalities. J. Comput. Appl. Math. 185, 166–173 (2006)
Zheng, L., Gou, Q.M.: The subgradient double projection algorithm for solving variational inequalities. Acta Math. Appl. Sin. 37, 968–975 (2014)
Han, D.R., Lo, H.K.: Two new self-adaptive projection methods for variational inequality problems. Comput. Math. Appl. 43, 1529–1537 (2002)
Langenberg, N.: An interior proximal method for a class of quasimonotone variational inequalities. J. Optim. Theory Appl. 155, 902–922 (2012)
Brito, A.S., Da Cruz Neto, J.X., Lopes, J.O., Oliveira, P.R.: Interior proximal method for quasiconvex programming problems and variational inequalities with linear constraints. J. Optim. Theory Appl. 154, 217–234 (2012)
Yekini, S., Qiao-Li, D., Dan, J.: Single projection method for pseudo-monotone variational inequality in Hilbert spaces. Optim. 68, 1385–409 (2019)
Morrey, C.B.: Quasiconvexity and lower semicontinuity of multiple intergrals. Pacific J. Math. 2, 25–53 (1952)
Morrey, C.B.: Multiple Integrals in the Calculus of Variations. Springer, Berlin (1952)
Ball, J.M.: Convexity conditions and existence theorems in nonlinear elasticity. Arch. Rational Mech. Anal. 86, 337–403 (1971)
Landes, R.: Quasiminotone versus pseudomonotone. Proc. R. Soc. Edinburgh Sect. A Math. 126(4), 705–717 (1996)
Danilidis, A.: Hadjisavvas: characterization of nonsmooth semistrictly quasiconvex and Strictly quasiconvex functions. J. Optim. Theory App. 102(3), 525–536 (1999)
Hadjisavvas, N., Schaible, S.: Quasimonotone variational inequalities in Banach spaces. J. Optim. Theory Appl. 90(1), 95–111 (1996)
Ye, M.L., He, Y.R.: A double projection method for solving variational inequalities without monotonicity. Comput. Optim. Appl. 60, 141–150 (2015)
Hu, X., Wang, J.: Solving pseudomonotone variational inequalities and pseudoconvex optimization problems using the projection neural network. IEEE Trans. Neural Netw. 17, 1487–1499 (2006)
Sun, D.F.: A new step-size skill for solving a class of nonlinear equations. J. Comput. Math. 13, 357–368 (1995)
Liu, H.W., Yang, J.: Weak convergence of iterative methods for solving quasimonotone variational inequalities. Comput. Optim. Appl. 77, 491–508 (2020)
Facchinei, F., Pang, J.S.: Finite-Dimensional Variational Inequality and Complementarity Problems, Volume I and II. Springer Series in Operations Research, (2003)
Zhu, T., Yu, Z.G.: A simple proof for some important properties of the projection mapping. Math. Inequal. Appl. 7, 453–456 (2004)
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The authors would like to thank the referees and the editor, for their comments, which greatly improved the presentation of this paper.
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The work is supported by grant National Natural Science Foundation of China (NSFC) 11971238.
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Jia, X., Xu, L. A projection-like method for quasimonotone variational inequalities without Lipschitz continuity. Optim Lett 16, 2387–2403 (2022). https://doi.org/10.1007/s11590-022-01874-w
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DOI: https://doi.org/10.1007/s11590-022-01874-w