Reflection-projection method for convex feasibility problems with an obtuse cone

被引:31
作者
Bauschke, HH [1 ]
Kruk, SG
机构
[1] Univ Guelph, Dept Math & Stat, Guelph, ON N1G 2W1, Canada
[2] Oakland Univ, Dept Math & Stat, Rochester, MI 48063 USA
[3] Fields Inst, Toronto, ON, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
convex feasibility problems; obtuse cones; projection methods; self-dual cones;
D O I
10.1023/B:JOTA.0000025708.31430.22
中图分类号
C93 [管理学]; O22 [运筹学];
学科分类号
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要
The convex feasibility problem asks to find a point in the intersection of finitely many closed convex sets in Euclidean space. This problem is of fundamental importance in the mathematical and physical sciences, and it can be solved algorithmically by the classical method of cyclic projections. In this paper, the case where one of the constraints is an obtuse cone is considered. Because the nonnegative orthant as well as the set of positive-semidefinite symmetric matrices form obtuse cones, we cover a large and substantial class of feasibility problems. Motivated by numerical experiments, the method of reflection-projection is proposed: it modifies the method of cyclic projections in that it replaces the projection onto the obtuse cone by the corresponding reflection. This new method is not covered by the standard frameworks of projection algorithms because of the reflection. The main result states that the method does converge to a solution whenever the underlying convex feasibility problem is consistent. As prototypical applications, we discuss in detail the implementation of two-set feasibility problems aiming to find a nonnegative [resp. positive semidefinite] solution to linear constraints in R-n [resp. in S-n, the space of symmetric n x n matrices] and we report on numerical experiments. The behavior of the method for two inconsistent constraints is analyzed as well.
引用
收藏
页码:503 / 531
页数:29
相关论文
共 44 条
[21]  
Goebel K., 1990, Topics on Metric Fixed Points Theory
[22]   THE RELAXATION METHOD FOR SOLVING SYSTEMS OF LINEAR INEQUALITIES [J].
GOFFIN, JL .
MATHEMATICS OF OPERATIONS RESEARCH, 1980, 5 (03) :388-414
[23]  
Golub G.H., 2013, Matrix Computations, V4th
[24]  
Groetsch C.W., 1977, Monographs and Textbooks in Pure and Applied Mathematics, V37
[25]   Barrier functions in interior point methods [J].
Guler, O .
MATHEMATICS OF OPERATIONS RESEARCH, 1996, 21 (04) :860-885
[26]  
Horn R., 1985, Matrix Analysis, DOI [DOI 10.1017/CBO9780511810817, 10.1017/CBO9780511810817]
[27]   Monotone gram matrices and deepest surrogate inequalities in accelerated relaxation methods for convex feasibility problems [J].
Kiwiel, KC .
LINEAR ALGEBRA AND ITS APPLICATIONS, 1997, 252 (1-3) :27-33
[28]   Surrogate projection methods for finding fixed points of firmly nonexpansive mappings. [J].
Kiwiel, KC ;
Lopuch, B .
SIAM JOURNAL ON OPTIMIZATION, 1997, 7 (04) :1084-1102
[29]   The efficiency of subgradient projection methods for convex optimization .2. Implementations and extensions [J].
Kiwiel, KC .
SIAM JOURNAL ON CONTROL AND OPTIMIZATION, 1996, 34 (02) :677-697
[30]  
KRUK S, 2001, THESIS U WATERLOO