In this paper we consider a linear programming problem with the underlying matrix unimodular, and the other data integer. Given arbitrary near optimum feasible solutions to the primal and the dual problems, we obtain conditions under which statements can be made about the value of certain variables in optimal vertices. Such results have applications to the problem of determining the stopping criterion in interior point methods like the primal—dual affine scaling method and the path following methods for linear programming.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47926/1/10107_2005_Article_BF01581235.pd
A modification of Snyman's interior feasible direction method for linear programming is proposed and...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
Tsuchiya and Muramatsu recently proved that the affine-scaling algorithm for linear programming gene...
This work concerns a method for identifying an optimal basis for linear programming problems in the ...
AbstractAn approach is proposed to generate a vertex solution while using a primal-dual interior poi...
AbstractA new feasible direction method for linear programming problems is presented. The method is ...
A new initialization or `Phase I' strategy for feasible interior point methods for linear programmin...
Many issues that are crucial for an efficient implementation of an interior point algorithm are addr...
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
In this paper the abstract of the thesis "New Interior Point Algorithms in Linear Programming&...
AbstractThe problem of finding the middle of a feasible region defined by solutions to a set of line...
AbstractWe give a definition of the normal form of an optimal solution of a linear programming probl...
The fundamental theorem of linear programming (LP) states that every feasible linear program that is...
A popular approach in combinatorial optimization is to model problems as integer linear programs. Id...
AbstractThis paper studies the difference between finite-dimensional linear programming problems and...
A modification of Snyman's interior feasible direction method for linear programming is proposed and...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
Tsuchiya and Muramatsu recently proved that the affine-scaling algorithm for linear programming gene...
This work concerns a method for identifying an optimal basis for linear programming problems in the ...
AbstractAn approach is proposed to generate a vertex solution while using a primal-dual interior poi...
AbstractA new feasible direction method for linear programming problems is presented. The method is ...
A new initialization or `Phase I' strategy for feasible interior point methods for linear programmin...
Many issues that are crucial for an efficient implementation of an interior point algorithm are addr...
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
In this paper the abstract of the thesis "New Interior Point Algorithms in Linear Programming&...
AbstractThe problem of finding the middle of a feasible region defined by solutions to a set of line...
AbstractWe give a definition of the normal form of an optimal solution of a linear programming probl...
The fundamental theorem of linear programming (LP) states that every feasible linear program that is...
A popular approach in combinatorial optimization is to model problems as integer linear programs. Id...
AbstractThis paper studies the difference between finite-dimensional linear programming problems and...
A modification of Snyman's interior feasible direction method for linear programming is proposed and...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
Tsuchiya and Muramatsu recently proved that the affine-scaling algorithm for linear programming gene...