Primal interior-point method for large sparse minimax optimization

Ladislav Lukšan; Ctirad Matonoha; Jan Vlček

Kybernetika (2009)

  • Volume: 45, Issue: 5, page 841-864
  • ISSN: 0023-5954

Abstract

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In this paper, we propose a primal interior-point method for large sparse minimax optimization. After a short introduction, the complete algorithm is introduced and important implementation details are given. We prove that this algorithm is globally convergent under standard mild assumptions. Thus the large sparse nonconvex minimax optimization problems can be solved successfully. The results of extensive computational experiments given in this paper confirm efficiency and robustness of the proposed method.

How to cite

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Lukšan, Ladislav, Matonoha, Ctirad, and Vlček, Jan. "Primal interior-point method for large sparse minimax optimization." Kybernetika 45.5 (2009): 841-864. <http://eudml.org/doc/37692>.

@article{Lukšan2009,
abstract = {In this paper, we propose a primal interior-point method for large sparse minimax optimization. After a short introduction, the complete algorithm is introduced and important implementation details are given. We prove that this algorithm is globally convergent under standard mild assumptions. Thus the large sparse nonconvex minimax optimization problems can be solved successfully. The results of extensive computational experiments given in this paper confirm efficiency and robustness of the proposed method.},
author = {Lukšan, Ladislav, Matonoha, Ctirad, Vlček, Jan},
journal = {Kybernetika},
keywords = {unconstrained optimization; large-scale optimization; minimax optimization; nonsmooth optimization; interior-point methods; modified Newton methods; variable metric methods; computational experiments; interior-point methods; minimax optimization; unconstrained optimization; computational experiments},
language = {eng},
number = {5},
pages = {841-864},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Primal interior-point method for large sparse minimax optimization},
url = {http://eudml.org/doc/37692},
volume = {45},
year = {2009},
}

TY - JOUR
AU - Lukšan, Ladislav
AU - Matonoha, Ctirad
AU - Vlček, Jan
TI - Primal interior-point method for large sparse minimax optimization
JO - Kybernetika
PY - 2009
PB - Institute of Information Theory and Automation AS CR
VL - 45
IS - 5
SP - 841
EP - 864
AB - In this paper, we propose a primal interior-point method for large sparse minimax optimization. After a short introduction, the complete algorithm is introduced and important implementation details are given. We prove that this algorithm is globally convergent under standard mild assumptions. Thus the large sparse nonconvex minimax optimization problems can be solved successfully. The results of extensive computational experiments given in this paper confirm efficiency and robustness of the proposed method.
LA - eng
KW - unconstrained optimization; large-scale optimization; minimax optimization; nonsmooth optimization; interior-point methods; modified Newton methods; variable metric methods; computational experiments; interior-point methods; minimax optimization; unconstrained optimization; computational experiments
UR - http://eudml.org/doc/37692
ER -

References

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