TY - JOUR
T1 - A unified framework of some proximal-based decomposition methods for monotone variational inequalities with separable structures
AU - He, Bingsheng
AU - Yuan, Xiaoming
N1 - Copyright:
Copyright 2013 Elsevier B.V., All rights reserved.
PY - 2012/10
Y1 - 2012/10
N2 - Some existing decomposition methods for solving a class of variational inequalities (VIs) with separable structures are closely related to the classical proximal point algorithm (PPA), as their decomposed sub-VIs are regularized by proximal terms. Differing in whether the generated sub-VIs are suitable for parallel computation, these proximal-based methods can be categorized into parallel decomposition methods and alternating decomposition methods. This paper generalizes these methods and thus presents a unified framework of proximal-based decomposition methods for solving this class of VIs, in both exact and inexact versions. Then, for various special cases of the unified framework, we analyze respective strategies for fulfilling a condition that ensures the convergence, which are realized by determining appropriate proximal parameters. Moreover, some concrete numerical algorithms for solving this class of VIs are derived. In particular, the inexact version of this unified framework gives rise to some implementable algorithms that allow the involved sub-VIs to be solved under some favorable criteria developed in PPA literature.
AB - Some existing decomposition methods for solving a class of variational inequalities (VIs) with separable structures are closely related to the classical proximal point algorithm (PPA), as their decomposed sub-VIs are regularized by proximal terms. Differing in whether the generated sub-VIs are suitable for parallel computation, these proximal-based methods can be categorized into parallel decomposition methods and alternating decomposition methods. This paper generalizes these methods and thus presents a unified framework of proximal-based decomposition methods for solving this class of VIs, in both exact and inexact versions. Then, for various special cases of the unified framework, we analyze respective strategies for fulfilling a condition that ensures the convergence, which are realized by determining appropriate proximal parameters. Moreover, some concrete numerical algorithms for solving this class of VIs are derived. In particular, the inexact version of this unified framework gives rise to some implementable algorithms that allow the involved sub-VIs to be solved under some favorable criteria developed in PPA literature.
KW - Alternating
KW - Decomposition
KW - Parallel
KW - Proximal point algorithm
KW - Variational inequality
UR - http://www.ybook.co.jp/online2/oppjo/vol8/p817.html
UR - http://www.scopus.com/inward/record.url?scp=84875010693&partnerID=8YFLogxK
M3 - Journal article
AN - SCOPUS:84875010693
SN - 1348-9151
VL - 8
SP - 817
EP - 844
JO - Pacific Journal of Optimization
JF - Pacific Journal of Optimization
IS - 4
ER -