An inexact method of partial inverses and a parallel bundle method

被引:10
作者
Burachik, RS
Sagastizábal, C
Scheimberg, S
机构
[1] IMPA, BR-22460320 Rio De Janeiro, Brazil
[2] Univ Fed Rio de Janeiro, COPPE, Engn Sistemas & Comp, BR-21941972 Rio de Janeiro, Brazil
[3] Univ Fed Rio de Janeiro, COPPE, Inst Matemat Engn Sistemas & Comp, BR-21941972 Rio de Janeiro, Brazil
关键词
maximal monotone operator; splitting methods; enlargement of a maximal monotone operator; hybrid proximal methods; parallel bundle methods;
D O I
10.1080/10556780500094887
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
For a maximal monotone operator T on a Hilbert space H and a closed subspace A of H, we consider the problem of finding (x, y is an element of T (x )) satisfying x is an element of A and y is an element of A(perpendicular to) . An equivalent formulation of this problem makes use of the partial inverse operator of Spingarn. The resulting generalized equation can be solved by using the proximal point algorithm. We consider instead the use of hybrid proximal methods. Hybrid methods use enlargements of operators, close in spirit to the concept of epsilon-subdifferentials. We characterize the enlargement of the partial inverse operator in terms of the enlargement of T itself. We present a new algorithm of resolution that combines Spingarn and hybrid methods, we prove for this method global convergence only assuming existence of solutions and maximal monotonicity of T. We also show that, under standard assumptions, the method has a linear rate of convergence. For the important problem of finding a zero of a sum of maximal monotone operators T-1,...,T-m , we present a highly parallelizable scheme. Finally, we derive a parallel bundle method for minimizing the sum of polyhedral functions.
引用
收藏
页码:385 / 400
页数:16
相关论文
共 16 条
[1]  
Bonnans J.-F., 2006, Numerical Optimization: Theoretical and Practical Aspects
[2]  
Burachik RS, 1999, LECT NOTES ECON MATH, V477, P49
[3]  
Burachik RS, 1999, APPL OPTIMIZAT, V22, P25
[4]   Enlargement of monotone operators with applications to variational inequalities [J].
Burachik, RS ;
Iusem, AN ;
Svaiter, BF .
SET-VALUED ANALYSIS, 1997, 5 (02) :159-180
[5]   ON THE DOUGLAS-RACHFORD SPLITTING METHOD AND THE PROXIMAL POINT ALGORITHM FOR MAXIMAL MONOTONE-OPERATORS [J].
ECKSTEIN, J ;
BERTSEKAS, DP .
MATHEMATICAL PROGRAMMING, 1992, 55 (03) :293-318
[6]   PROXIMAL DECOMPOSITION ON THE GRAPH OF A MAXIMAL MONOTONE OPERATOR [J].
MAHEY, P ;
OUALIBOUCH, S ;
TAO, PD .
SIAM JOURNAL ON OPTIMIZATION, 1995, 5 (02) :454-466
[7]   A relationship between cerebellar Purkinje cells and spatial working memory demonstrated in a lurcher/chimera mouse model system [J].
Martin, LA ;
Escher, T ;
Goldowitz, D ;
Mittleman, G .
GENES BRAIN AND BEHAVIOR, 2004, 3 (03) :158-166
[8]  
Moreau JJ, 1965, Bull. Soc. Math. Fr, V93, P273, DOI DOI 10.24033/BSMF.1625
[9]   Epsilon-proximal decomposition method [J].
Ouorou, A .
MATHEMATICAL PROGRAMMING, 2004, 99 (01) :89-108
[10]  
Rockafellar R. T., 1976, Mathematics of Operations Research, V1, P97, DOI 10.1287/moor.1.2.97