The Peaceman-Rachford method for small mesh increments
نویسندگان
چکیده
منابع مشابه
Stochastic Strictly Contractive Peaceman-Rachford Splitting Method
In this paper, we propose a couple of new Stochastic Strictly Contractive PeacemanRachford Splitting Method (SCPRSM), called Stochastic SCPRSM (SS-PRSM) and Stochastic Conjugate Gradient SCPRSM (SCG-PRSM) for large-scale optimization problems. The two types of Stochastic PRSM algorithms respectively incorporate stochastic variance reduced gradient (SVRG) and conjugate gradient method. Stochasti...
متن کاملOn the Effects of Scaling of the Peaceman-Rachford Method
The alternating direction method of Peaceman and Rachford is considered for elliptic difference schemes of second order and with two independent variables. An earlier result of the author's on the rapid convergence of multi-parameter noncommutative problems is described and a connection is established between that result and theorems on optimal scaling of band matrices. Simple algorithms to dec...
متن کاملA Strictly Contractive Peaceman-Rachford Splitting Method for Convex Programming
In this paper, we focus on the application of the Peaceman-Rachford splitting method (PRSM) to a convex minimization model with linear constraints and a separable objective function. Compared to the Douglas-Rachford splitting method (DRSM), another splitting method from which the alternating direction method of multipliers originates, PRSM requires more restrictive assumptions to ensure its con...
متن کاملA semi-proximal-based strictly contractive Peaceman-Rachford splitting method∗
The Peaceman-Rachford splitting method is very efficient for minimizing sum of two functions each depends on its variable, and the constraint is a linear equality. However, its convergence was not guaranteed without extra requirements. Very recently, He et al. (SIAM J. Optim. 24: 1011 1040, 2014) proved the convergence of a strictly contractive Peaceman-Rachford splitting method by employing a ...
متن کاملConvergence analysis of the Peaceman-Rachford splitting method for nonsmooth convex optimization
In this paper, we focus on the convergence analysis for the application of the PeacemanRachford splitting method to a convex minimization model whose objective function is the sum of a smooth and nonsmooth convex functions. The sublinear convergence rate in term of the worst-case O(1/t) iteration complexity is established if the gradient of the smooth objective function is assumed to be Lipschi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Mathematical Analysis and Applications
سال: 1965
ISSN: 0022-247X
DOI: 10.1016/0022-247x(65)90086-7