 
Summary: A New Infeasible InteriorPoint Algorithm
for Linear Programming
Miguel Arg´aez
mar@math.utep.edu
Leticia Vel´azquez
leti@math.utep.edu
Department of Mathematical Sciences
The University of Texas at El Paso
El Paso, Texas 799680514
ABSTRACT
In this paper we present an infeasible pathfollowing interior
point algorithm for solving linear programs using a relaxed
notion of the central path, called quasicentral path, as a
central region. The algorithm starts from an infeasible point
which satisfies that the norm of the dual condition is less
than the norm of the primal condition. We use weighted
sets as proximity measures of the quasicentral path, and a
new merit function for making progress toward this central
region. We test the algorithm on a set of NETLIB problems
