Numerical Experiments with a Primal-Dual Algorithm for Solving Quadratic Problems

Derkaoui Orkia, Lehireche Ahmed


This paper provides a new variant of primal-dual interior-point method for solving a SemiDefinite Program (SDP). We use the PDIPA (primal-dual interior-point algorithm) solver entitled SDPA (SemiDefinite Programming Algorithm). This last uses a classical Newton descent method to compute the predictor-corrector search direction. The difficulty is in the computation of this line-search, it induces high computational costs. Here, instead we adopt a new procedure to implement another way to determine the step-size along the direction which is more efficient than classical line searches. This procedure consists in the computation of the step size in order to give a significant decrease along the descent line direction with a minimum cost. With this procedure we obtain à new variant of SDPA. The comparison of the results obtained with the classic SDPA and our new variant is promising.


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Paper Citation

in Harvard Style

Orkia D. and Ahmed L. (2016). Numerical Experiments with a Primal-Dual Algorithm for Solving Quadratic Problems . In Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-758-171-7, pages 204-209. DOI: 10.5220/0005813802040209

in Bibtex Style

author={Derkaoui Orkia and Lehireche Ahmed},
title={Numerical Experiments with a Primal-Dual Algorithm for Solving Quadratic Problems},
booktitle={Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},

in EndNote Style

JO - Proceedings of 5th the International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Numerical Experiments with a Primal-Dual Algorithm for Solving Quadratic Problems
SN - 978-989-758-171-7
AU - Orkia D.
AU - Ahmed L.
PY - 2016
SP - 204
EP - 209
DO - 10.5220/0005813802040209