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博碩士論文 etd-0623109-000852 詳細資訊
Title page for etd-0623109-000852
論文名稱
Title
反強單調算子和變分不等式
Inverse strongly monotone operators and variational inequalities
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
24
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2009-06-16
繳交日期
Date of Submission
2009-06-23
關鍵字
Keywords
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
convergence, iteration, projection, minimization, Lipschitzian operator, Variational inequality, inverse strongly monotone, averaged mapping, strongly monotone, monotone, fixed point
統計
Statistics
本論文已被瀏覽 5716 次,被下載 1325
The thesis/dissertation has been browsed 5716 times, has been downloaded 1325 times.
中文摘要
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。
Abstract
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.
目次 Table of Contents
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
參考文獻 References
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[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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