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Résumé:
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This thesis focuses on several aspects of data perturbation for Linear Programming. Classical questions of degeneracy and post-optimal analysis are given a unified presentation, in a view of new interior point methods of linear programming. The performance of these methods is compared to the simplex algorithm; interior point methods are shown to alleviate some difficulties of representation and solution of linear programs. An affine scaling algorithm is implemented in conjunction with a simple rounding heuristic to asses the benefit of interior point trajectories to provide approximate solutions of linear integer programming. |
