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Superlinear convergence of a trust region-type successive linear programming method

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Abstract

The convergence rate of the SLP method suggested in Ref. 1 is discussed for composite nondifferentiable optimization problems. A superlinear rate is assured under a growth condition, and it is further strengthened to a quadratic rate if the inside function is twice differentiable. Several sufficient conditions are given which make the growth condition true. These conditions can be relaxed considerably in practical use.

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Communicated by A. V. Fiacco

This research was supported in part by the National Natural Science Foundation of China.

The author is grateful to Professor E. Sachs, Universität Trier, Trier, West Germany, for his helpful suggestions.

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Zhang, J.Z. Superlinear convergence of a trust region-type successive linear programming method. J Optim Theory Appl 61, 295–310 (1989). https://doi.org/10.1007/BF00962802

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