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A Globally Convergent Infeasible Interior Point Method
for Linear Constrained Convex Programming

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R.Q. do Nascimento and P. R. Oliveira

We present an infeasible interior point method for
linear constrained convex programming, which has finite
convergence for an epsilon-solution. The method is a
variant of the infeasible interior point method
developed for linear programming. An interesting fact
is that when the primal problem is consistent, its dual
is asymptotically consistently feasible and, if the
matrix A has full rank, the sequence generated by the
algorithm is bounded. The results obtained on the
boundedness were based on the theory developed for
monotone operators and complementarity problems,
besides some hypothesis on asymptotic consistency
sequences and boundedly asymptotically solvable
problems. This method was very efficient when solving
problems of geometric programming in literature.
R.T. PESC/COPPE-Federal University of Rio de Janeiro
C.P. 68511, 20771-421, Rio de Janeiro, Brazil, 04/2000

Contact: poliveir@cos.ufrj.br