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研究生:紀文德
研究生(外文):Wen-te Chi
論文名稱:反強單調算子和變分不等式
論文名稱(外文):Inverse strongly monotone operators and variational inequalities
指導教授:徐洪坤
指導教授(外文):Hong-Kun Xu
學位類別:碩士
校院名稱:國立中山大學
系所名稱:應用數學系研究所
學門:數學及統計學門
學類:數學學類
論文種類:學術論文
論文出版年:2009
畢業學年度:97
語文別:英文
論文頁數:24
中文關鍵詞:變分不等式固定點單調強單調Lipschitzian算子反強單調平均映像投影疊代收斂最小值
外文關鍵詞:convergenceiterationprojectionminimizationLipschitzian operatorVariational inequalityinverse strongly monotoneaveraged mappingstrongly monotonemonotonefixed point
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  • 被引用被引用:0
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  • 下載下載:10
  • 收藏至我的研究室書目清單書目收藏:0
在這篇論文中,我們討論在強單調算子或反強單調算子下,單調變分不等式的存在收斂結果。我們將變分不等式問題等價於固定點問題以公式表示之,並使用固定點疊代法去解決原使變分不等式的問題。
在強單調的部分:我們使用 Banach’s 壓縮原理定義疊代序列;在反強單調的部分:我們使用平均映像的技巧定義疊代序列,在這兩部分我們都利用疊代法證明是強收斂,最後應用於解決最小值的問題。
In this paper, we report existing convergence results on monotone variational inequalities where the governing monotone operators are either strongly monotone or inverse strongly monotone. We reformulate the variational inequality problem as
an equivalent fixed point problem and then use fixed point iteration method to solve the original variational inequality problem. In the case of strong monotonicity case we use the Banach’s contraction principle to define out iteration sequence; while in the case of inverse strong monotonicity we use the technique of averaged mappings to define our iteration sequence. In both cases we prove strong convergence for our
iteration methods. An application to a minimization problem is also included.
1 Introduction
2 Fixed Point Theorems
3 VI(F,C) Where F Is Strongly Monotone
4 VI(F,C) Where F Is Inverse Strongly Monotone
5 An Application in Optimization
6 References
[1] F. Facchinei, J.S. Pang, Finite-Dimensional Variational Inequalities and Complementarity Problems, Springer Series in Operations Research, Springer-Verlag (2003).
[2] D.R. Han, H.K. Lo, Solving non-additive traffic assignment problems: A descent method for co-coercive variational inequalities, European Journal
of Operational Research 159(2004), 529-544.
[3] B.S. He, A projection and contraction method for a class of linear complementarity problems and its application in convex quadratic programming,
Applied Mathematics and Optimization 25(3)(1992), 247-262.
[4] H. Iiduka, W. Takahashi, Strong Convergence Theorems for Nonexpansive Nonself-Mappings and Inverse-Strongly-Monotone Mappings, Journal of
Convex Analysis 11(2004), 69-79.
[5] M. Li, L.-Z. Liao and X.-M. Yuan, A modified descent method for co-coercive variational inequalities, European Journal of Operations Research 189(2008),
310-323.
[6] P. Marcotte, J.H. Wu, On the convergence of projection methods: Application to the decomposition of affine variational inequalities, Journal of Optimization Theory and Applications 85(2)(1995), 347-362.
[7] A. Ruszczynski, Nonlinear Optimization, Princeton, N.J. : Princeton University Press, 2006.
[8] W. Takahashi, Nonlinear variational inequalities and fixed point theorems, J. Math. Soc. Japan 28(1976), 168-181.
[9] W. Takahashi, M. Toyoda, Weak convergence theorems for nonexpansive mappings and monotone mappings, J. Optim. Theory Appl. 118(2003), 417-
428.
[10] Lu-Chuan Zeng and Jen-Chih Yao, Strong convergence theorem by an extragradient method for fixed point problems and variational inequality
problems, Taiwanese J. of Mathematics 10(2006), 1293-1303.
[11] D. L. Zhu and P. Marcotte, Co-coercivity and its rule in the convergence of iterative schemes for solving variational inequalities, SIAM J. Optimization
6(1996), 714-726.
[12] T. Zhu, Z.G. Yu, A simple proof for some important properites of the projection mapping, Mathematical Inequalities and Applications 7(3)(2004), 453-
456.
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