An interior-point penalty active-set trust-region algorithm
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文摘
In this work, an active set strategy is used together with a Coleman–Li strategy and penalty method to transform a general nonlinear programming problem with bound on the variables to unconstrained optimization problem with bound on the variables. A trust-region globalization strategy is used to compute a step. A global convergence theory for the proposed algorithm is presented under credible assumptions.

Prefatory numerical experiment on the algorithm is presented. The rendering of the algorithm is reported on some classical problem.

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