Improving complexity of Karmarkar's approach for linear programming

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Djamel Benterki Mousaab Bouafia


In this paper, we are interested in the performance of Karmarkar's projective algorithm for linear programming. Based on the work of Schrijver, we offer a new displacement step better than Schrijver's one which led to a moderate improvement in the behavior of the algorithm shift. We show later that the algorithm converges after \(\frac{n}{1-\log\left( 2\right) +(\frac{nr^{2}}{10})}\log\big( \frac{c^{t}e_{n}}{\varepsilon}\big) \) iterations.  This purpose is confirmed by numerical experiments showing the efficiency of the obtained algorithm, which are presented in the end of the paper.

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linear programming; interior point method; potential function