Computational behavior of a feasible direction method for linear programming
نویسندگان
چکیده
منابع مشابه
Computational behavior of a feasible direction method for linear programming
We discuss a finite method of feasible directions for linear programs. The method begins with a BFS (basic feasible solution) and constructs a profitable direction by combining the updated columns of several nonbasic variables eligible to enter. Moving in this direction as far as possible, while retaining feasibility, leads to a point which is not in general a basic solution of the original pro...
متن کاملAn Interior Feasible Direction Method with Constraint Projections for Linear Programming
-A new feasible direction method for linear programming problems is presented. The method is not boundary following. The method proceeds from a feasible interior point in a direction that improves the objective function until a point on a constraint surface is met. At this point searches are initiated in the hyperplane of constant function value by using projections of the bounding constraints ...
متن کاملA New Alternating Direction Method for Linear Programming
It is well known that, for a linear program (LP) with constraint matrix A ∈ Rm×n, the Alternating Direction Method of Multiplier converges globally and linearly at a rate O((‖A‖F +mn) log(1/ )). However, such a rate is related to the problem dimension and the algorithm exhibits a slow and fluctuating “tail convergence” in practice. In this paper, we propose a new variable splitting method of LP...
متن کاملAlternating Direction Method of Multipliers for Linear Programming
Recently the alternating direction method of multipliers (ADMM) has been widely used for various applications arising in scientific computing areas. Most of these application models are, or can be easily reformulated as, linearly constrained convex minimization models with separable nonlinear objective functions. In this note we show that ADMM can also be easily used for the canonical linear pr...
متن کاملA feasible direction interior point algorithm for nonlinear semidefinite programming
We present a new algorithm for nonlinear semidefinite programming, based on the iterative solution in the primal and dual variables of Karush-KuhnTucker optimality conditions, which generates a feasible decreasing sequence. At each iteration, two linear systems with the same matrix are solved to compute a feasible descent direction and then an inexact line search is performed in order to determ...
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: European Journal of Operational Research
سال: 1989
ISSN: 0377-2217
DOI: 10.1016/0377-2217(89)90424-4