A nonmonotone filter method for nonlinear optimization |
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Authors: | Chungen Shen Sven Leyffer Roger Fletcher |
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Institution: | 1. Department of Applied Mathematics, Shanghai Finance University, Shanghai, 201209, China 2. Mathematics and Computer Science Division, Argonne National Laboratory, Argonne, IL, 60439, USA 3. Mathematics Department, University of Dundee, Dundee, UK
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Abstract: | We propose a new nonmonotone filter method to promote global and fast local convergence for sequential quadratic programming algorithms. Our method uses two filters: a standard, global g-filter for global convergence, and a local nonmonotone l-filter that allows us to establish fast local convergence. We show how to switch between the two filters efficiently, and we prove global and superlinear local convergence. A special feature of the proposed method is that it does not require second-order correction steps. We present preliminary numerical results comparing our implementation with a classical filter SQP method. |
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