Resolution of semidefinite linear complementarity problem (SDLCP) using new interior point methods based on kernel fonctions .
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Date
2023
Authors
Nabila Abdessemed
Journal Title
Journal ISSN
Volume Title
Publisher
University of Batna 2
Abstract
In this thesis, we propose a new kernel function which has a great influence
on the improvement of the complexity and a crucial role concerning the
introduction of a new class of search directions to solve the monotone
semidefinite linear complementarity problem (SDLCP) by primal-dual following
path interior point algorithm. This directions are not orthogonal what makes
the study more difficult.
A theoretical, algorithmic and numerical study was carried out. We obtain
currently best known iteration bound for the algorithm with large-update
method, namely O (√n(log n)
2
log(n/ε)). The implementation of the algorithm
showed a great improvement concerning the time and the number of iterations.