Primal interior point method for minimization of generalized minimax functions

Ladislav Lukšan; Ctirad Matonoha; Jan Vlček

Displaying similar documents to “Primal interior point method for minimization of generalized minimax functions”

Primal interior-point method for large sparse minimax optimization

Ladislav Lukšan, Ctirad Matonoha, Jan Vlček (2009)

Kybernetika

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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...

An accurate active set Newton algorithm for large scale bound constrained optimization

Li Sun, Guoping He, Yongli Wang, Changyin Zhou (2011)

Applications of Mathematics

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A new algorithm for solving large scale bound constrained minimization problems is proposed. The algorithm is based on an accurate identification technique of the active set proposed by Facchinei, Fischer and Kanzow in 1998. A further division of the active set yields the global convergence of the new algorithm. In particular, the convergence rate is superlinear without requiring the strict complementarity assumption. Numerical tests demonstrate the efficiency and performance of the...

An active set strategy based on the multiplier function or the gradient

Li Sun, Liang Fang, Guoping He (2010)

Applications of Mathematics

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We employ the active set strategy which was proposed by Facchinei for solving large scale bound constrained optimization problems. As the special structure of the bound constrained problem, a simple rule is used for updating the multipliers. Numerical results show that the active set identification strategy is practical and efficient.