Add to ORKGExisting software implementations for solving Linear Programming (LP) models are all based on full matrix inversion operations involving every constraint in the model in every step. This linear algebra component in these systems makes it difficult to solve dense models even with moderate size, and it is also the source of accumulating roundoff errors affecting the accuracy of the output. We present a new Sphere method, SM-6, for LP not using any pivot steps. The method is currently undergoing computational tests
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In each iteration of the interior point method (IPM) at least one linear system has to be solved. T...
This note reports some experimental results on the inversion of real linear programming bases, with ...
1 Introduction Since their discovery [1] interior point methods (IPMs) have enjoyed well-deser-ved i...
Existing software implementations for solving Linear Programming (LP) models are all based on full m...
Interior point methods (IPM) are first introduced as an efficient polynomial time algorithm to solve...
The sphere method for solving linear programs operates with only a subset of constraints in the mode...
Primal &ndash dual interior &ndash point methods (IPMs) are distinguished for their exceptional theo...
Consider the linear program (LP): minimize z = cx, subject to Ax ≥ b, where A is an m × n matrix. Sp...
In this paper we describe a unified algorithmic framework for the interior point method (IPM) of sol...
Linear programming (LP) stands for an optimization of a linear objective function, subject to linear...
In the past fifteen years, research on Interior Point Methods (IPM) and their applications were ver...
With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to co...
A fast Newton method is proposed for solving linear programs with a very large ( 106) number of co...
The interior point method (IPM) is now well established as a competitive technique for solving very ...
Linear programming (LP) is one of the most widely-applied techniques in operations research. Many me...
In each iteration of the interior point method (IPM) at least one linear system has to be solved. T...
This note reports some experimental results on the inversion of real linear programming bases, with ...
1 Introduction Since their discovery [1] interior point methods (IPMs) have enjoyed well-deser-ved i...
Existing software implementations for solving Linear Programming (LP) models are all based on full m...
Interior point methods (IPM) are first introduced as an efficient polynomial time algorithm to solve...
The sphere method for solving linear programs operates with only a subset of constraints in the mode...
Primal &ndash dual interior &ndash point methods (IPMs) are distinguished for their exceptional theo...
Consider the linear program (LP): minimize z = cx, subject to Ax ≥ b, where A is an m × n matrix. Sp...
In this paper we describe a unified algorithmic framework for the interior point method (IPM) of sol...
Linear programming (LP) stands for an optimization of a linear objective function, subject to linear...
In the past fifteen years, research on Interior Point Methods (IPM) and their applications were ver...
With emphasis on computation, this book is a real breakthrough in the field of LP. In addition to co...
A fast Newton method is proposed for solving linear programs with a very large ( 106) number of co...
The interior point method (IPM) is now well established as a competitive technique for solving very ...
Linear programming (LP) is one of the most widely-applied techniques in operations research. Many me...
In each iteration of the interior point method (IPM) at least one linear system has to be solved. T...
This note reports some experimental results on the inversion of real linear programming bases, with ...
1 Introduction Since their discovery [1] interior point methods (IPMs) have enjoyed well-deser-ved i...