We consider an infeasible-interior-point algorithm, endowed with a finite termination scheme, applied to random linear programs generated according to a model of Todd. Such problems have degenerate optimal solutions, and possess no feasible starting point. We use no information regarding an optimal solution in the initialization of the algorithm. Our main result is that the expected number of iterations before termination with an exact optimal solution is O(n ln(n)). Keywords: Linear Programming, Average-Case Behavior, Infeasible-Interior-Point Algorithm. Running Title: Probabilistic Analysis of an LP Algorithm 1 Dept. of Management Sciences, University of Iowa. Supported by an Interdisciplinary Research Grant from the Center for Advance...
A phase-1-algorithm for interior-point-methods : worst-case and average-case behavior. - In: Operati...
A phase-1-algorithm for interior-point-methods : worst-case and average-case behavior. - In: Operati...
AbstractIn this paper we address the complexity of solving linear programming problems with a set of...
We consider the problem of finding an −optimal solution of a standard linear pro-gram with real data...
AbstractWe consider the problem of finding an ε-optimal solution of a standard linear program with r...
We consider the problem of finding an ε{lunate}-optimal solution of a standard linear program with ...
AbstractWe are interested in the average behavior of interior-point methods (IPMs) for linear progra...
: We provide a probabilistic analysis of the second order term that arises in pathfollowing algorith...
AbstractWe consider the problem of finding an ε-optimal solution of a standard linear program with r...
Due to the structure of the solution set, an exact solution to a linear program cannot be computed b...
AbstractExterior-point linear programming algorithms have been modelled as a Markov chain in order t...
AbstractExterior-point linear programming algorithms have been modelled as a Markov chain in order t...
As linear programs have grown larger and more complex, infeasible models are appearing more frequent...
In this paper we address the complexity of solving linear programming problems with a set of differe...
Introduction to Linear Programming Linear programming is a very important class of problems, both a...
A phase-1-algorithm for interior-point-methods : worst-case and average-case behavior. - In: Operati...
A phase-1-algorithm for interior-point-methods : worst-case and average-case behavior. - In: Operati...
AbstractIn this paper we address the complexity of solving linear programming problems with a set of...
We consider the problem of finding an −optimal solution of a standard linear pro-gram with real data...
AbstractWe consider the problem of finding an ε-optimal solution of a standard linear program with r...
We consider the problem of finding an ε{lunate}-optimal solution of a standard linear program with ...
AbstractWe are interested in the average behavior of interior-point methods (IPMs) for linear progra...
: We provide a probabilistic analysis of the second order term that arises in pathfollowing algorith...
AbstractWe consider the problem of finding an ε-optimal solution of a standard linear program with r...
Due to the structure of the solution set, an exact solution to a linear program cannot be computed b...
AbstractExterior-point linear programming algorithms have been modelled as a Markov chain in order t...
AbstractExterior-point linear programming algorithms have been modelled as a Markov chain in order t...
As linear programs have grown larger and more complex, infeasible models are appearing more frequent...
In this paper we address the complexity of solving linear programming problems with a set of differe...
Introduction to Linear Programming Linear programming is a very important class of problems, both a...
A phase-1-algorithm for interior-point-methods : worst-case and average-case behavior. - In: Operati...
A phase-1-algorithm for interior-point-methods : worst-case and average-case behavior. - In: Operati...
AbstractIn this paper we address the complexity of solving linear programming problems with a set of...