Abstract
A mechanism for proving global convergence in filter-SQP (sequence of quadratic programming) method with the nonlinear complementarity problem (NCP) function is described for constrained nonlinear optimization problem. We introduce an NCP function into the filter and construct a new SQP-filter algorithm. Such methods are characterized by their use of the dominance concept of multi-objective optimization, instead of a penalty parameter whose adjustment can be problematic. We prove that the algorithm has global convergence and superlinear convergence rates under some mild conditions.
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