期刊文献+

非Lipschitz集值混合变分不等式的一个投影次梯度方法 被引量:4

A Projected Subgradient Method for Non-Lipschitz Set-Valued Mixed Variational Inequalities
下载PDF
导出
摘要 建立了一个投影次梯度方法来求解一类集值混合变分不等式,其中相关的映象不必是Lipschitz连续的.在合适的条件下,证明了在Hilbert空间中该方法产生的序列强收敛于问题的唯一解. A projected subgradient method for solving a class of set-valued mixed variational in- equalities when the mapping was not necessarily Lipschitz was proposed. Under some suitable conditions, it is proved that the sequence generated by the method was strongly convergent to the unique solution of the problem in Hilbert spaces.
机构地区 四川大学数学系
出处 《应用数学和力学》 CSCD 北大核心 2011年第10期1254-1264,共11页 Applied Mathematics and Mechanics
基金 国家自然科学基金重点资助项目(70831005) 国家自然科学基金资助项目(10671135) 中央高校基本科研业务费资助项目(2009SCU11096)
关键词 集值混合变分不等式 投影次梯度方法 非Lipschitz映象 收敛性 set-valued mixed variational inequality projected subgradient method non-Lipschitz mapping convergence
  • 相关文献

参考文献28

  • 1Han W, Reddy B. On the finite element method for mixed variational inequalities arising in elastoplasticity[ J]. SIAM J Numer Anal, 1995, 32(6) : 1778-1807.
  • 2Cohen G. Nash equilibria: gradient and decomposition algorithms [J ]. Large Scale Systems, 1987, 12(2) : 173-184.
  • 3Facchinei F, Pang J S. Finite-Dimensional Variational Inequalities and Complementary Problems [ M ] New York- Springer-Verlag, 2003.
  • 4Iusem A N, Svaiter B F. A variant of Korpelevich' s method for solving variational inequalities with a new search strategy[J]. Optimization, 1997, 42(4) : 309-321.
  • 5Xia F Q, Huang N J, Liu Z B. A projected subgradient method for solving generalized mixed variational inequalities[J]. Oper Res Lett, 2008, 36(5 ): 537-542.
  • 6何诣然.一个关于混合变分不等式问题的投影算法[J].数学物理学报(A辑),2007,27(2):215-220. 被引量:10
  • 7Konnov I. A combined relaxation method for a class of nonlinear variational inequalities[ J]. Optimization, 2002, 51( 1 ): 127-143.
  • 8Mainge P E. Projected subgradient techniques and viscosity methods for optimization with variational inequality constraints [ J ]. European J Oper Res, 2010, 205 ( 3 ) : 501-505.
  • 9Anh P N, Muu L D, Strodiot J J. Generalized projection method for non-Lipschitz multivalued monotone variational inequalities[ J]. Acta Math Vietnam, 2009, 34( 1 ) : 67-79.
  • 10Farouq N E. Pseudomonotone variational inequalities: convergence of the auxiliary problem method[J]. J Optim Theory Appl, 2001, 111(2) : 306-325.

二级参考文献49

  • 1Goebel K, Kirk W A. Topics in Metric Fixed Point Theory [ M ]. Cambridge Studies in Advanced Mathematics. 28. Cambridge: Cambridge University Press, 1990.
  • 2Byrne C. A unified treatment of some iterative algorithms in signal processing and image reconstruction[ J]. Inverse Problems, 2004, 20( 1 ) : 103-120.
  • 3Censor Y, Motova A, Segal A. Perturbed projections and subgradient projections for the multiple-sets split feasibility problem [ J ]. J Math Anal Appl, 2007, 327 (2) : 1244-1256.
  • 4Cianciaruso F, Marino G, Muglia L, Yao Y. On a two-step algorithm for hierarchical fixed points and variational inequalities[ J]. J Inequalities and Appl, 2009, Article ID 208592, 13 pages, doi: 10.1155/2009/208692.
  • 5Cianciaruso F, Colao V, Muglia L, Xu H K. On an implicit hierarchical fixed point approach to variational inequalities [ J ]. Bull Austral Math Soc, 2009, 80 ( 1 ) : 117-124.
  • 6Malnge P E, Moudafi A. Strong convergence of an iterative method for hierarchical fixed point problems[J]. Pacific J Optim, 2007,3(3) : 529-538.
  • 7Marino G, Xu H K. A general iterative method for nonexpansive mappings in Hilbert space [J]. JMathAnalAppl, 2006, 318(1): 43-52.
  • 8Moudafi A. Krasnoselski-Mann iteration for hierarchical fixed point problems [ J ]. Inverse Problems, 2007, 23(4): 1635-1540.
  • 9Solodov M. An explicit descent method for bilevel convex optimization [ J ]. J Convex Anal, 2007, 14(2): 227-237.
  • 10Yao Y, Liou Y C. Weak and strong convergence of Krasnoselski-Mann iteration for hierarchi- cal fixed point problems[J]. Inverse Problems, 2008, 24( 1 ) : 15015-15022.

共引文献30

同被引文献8

引证文献4

二级引证文献2

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部