An Asynchronous Block-Parallel Algorithm for Separable Quadratic Programming Problems
نویسندگان
چکیده
منابع مشابه
An Algorithm for Solving Quadratic Programming Problems
Herein is investigated the method of solution of quadratic programming problems. The algorithm is based on the effective selection of constraints. Quadratic programming with constraintsequalities are solved with the help of an algorithm, so that matrix inversion is avoided, because of the more convenient organization of the Calculus. Optimal solution is determined in a finite number of iteratio...
متن کاملAn iterative method for tri-level quadratic fractional programming problems using fuzzy goal programming approach
Tri-level optimization problems are optimization problems with three nested hierarchical structures, where in most cases conflicting objectives are set at each level of hierarchy. Such problems are common in management, engineering designs and in decision making situations in general, and are known to be strongly NP-hard. Existing solution methods lack universality in solving these types of pro...
متن کاملA Block-parallel Conjugate Gradient Method for Separable Quadratic Programming Problems1
For a large-scale quadratic programming problem with separable objective function, a variant of the conjugate gradient method can effectively be applied to the dual problem. In this paper, we consider a block-parallel modification of the conjugate gradient method, which is suitable for implementation on a parallel computer. More precisely, the method proceeds in a block Jacobi manner and execut...
متن کاملLinear Time Algorithms for Some Separable Quadratic Programming Problems
A large class of separable quadratic programming problems is presented The problems in the class can be solved in linear time The class in cludes the separable convex quadratic transportation problem with a xed number of sources and separable convex quadratic programming with nonnegativity con straints and a xed number of linear equality constraints
متن کاملHAMSI: A Parallel Incremental Optimization Algorithm Using Quadratic Approximations for Solving Partially Separable Problems
We propose HAMSI, a provably convergent incremental algorithm for solving large-scale partially separable optimization problems that frequently emerge in machine learning and inferential statistics. The algorithm is based on a local quadratic approximation and hence allows incorporating a second order curvature information to speed-up the convergence. Furthermore, HAMSI needs almost no tuning, ...
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: Transactions of the Institute of Systems, Control and Information Engineers
سال: 1997
ISSN: 1342-5668,2185-811X
DOI: 10.5687/iscie.10.248