A trust-funnel method for nonlinear optimization problems with general nonlinear constraints and its application to derivative-free optimization

A trust-funnel method is proposed for solving nonlinear optimization problems with general nonlinear constraints. It extends the one presented by Gould and Toint (Math. Prog., 122(1):155-196, 2010), originally proposed for equality-constrained optimization problems only, to problems with both equality and inequality constraints and where simple bounds are also considered. As the original one, our method makes use of neither filter nor penalty functions and consider the objective function and the constraints as independently as possible. To handle the bounds, an active-set approach is employed. At last, we exploit and incorporate techniques developed for derivative-free optimization to obtain a final method that can also be used to solve problems where the derivatives are unavailable or are available at a prohibitive cost.

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Report naXys-03-2015, Namur Center for Complex Systems, University of Namur, Namur, Belgium

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