Some Disadvantages of a Mehrotra-Type Primal-Dual Corrector Interior Point Algorithm for Linear Programming

Coralia Cartis (ccartiscomlab.ox.ac.uk)

Abstract: The Primal-Dual Corrector (PDC) algorithm that we propose computes on each iteration a corrector direction in addition to the direction of the standard primal-dual path-following interior point method (Kojima et al., 1989) for Linear Programming (LP), in an attempt to improve performance. The new iterate is chosen by moving along the sum of these directions, from the current iterate. This technique is similar to the construction of Mehrotra's highly popular predictor-corrector algorithm (Mehrotra, 1991). We present examples, however, that show that the PDC algorithm may fail to converge to a solution of the LP problem, in both exact and finite arithmetic, regardless of the choice of stepsize that is employed. The cause of this bad behaviour is that the correctors exert too much influence on the direction in which the iterates move.

Keywords: Mehrotra predictor-corrector algorithm, interior point methods, linear programming

Category 1: Linear, Cone and Semidefinite Programming (Linear Programming )

Citation: Technical Report 04/27 Oxford University Computing Laboratory Numerical Analysis Group Wolfson Building Parks Road Oxford OX1 3QD

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Entry Submitted: 02/17/2005
Entry Accepted: 02/17/2005
Entry Last Modified: 02/17/2005

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