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Nonmonotonic back-tracking trust region interior point algorithm for linear constrained optimization. (English) Zbl 1028.65065
A modification of the trust region interior point algorithm proposed by J. F. Bonnas and C. Pola [SIAM J. Optim. 7, 717-731 (1997; Zbl 0899.90146)] for linear constrained optimization is presented. A mixed strategy using both trust region and line-search techniques is adopted which swiches to back-tracking steps when a trial step produced by the trust region subproblem may be unacceptable. The global convergence and local convergence rate of the improved algorithm are established under some reasonable conditions.A nonmonotonic criterion is used to speed up the convergence progress in some ill-conditioned cases. The results of numerical experiments are reported to show the effectiveness of the proposed algorithm.

MSC:
65K05 Numerical mathematical programming methods
90C30 Nonlinear programming
90C51 Interior-point methods
Software:
GQTPAR
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References:
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