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| Author(s): |
John Lenon Cardoso Gardenghi
Total Authors: 1
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| Document type: | Master's Dissertation |
| Press: | São Paulo. |
| Institution: | Universidade de São Paulo (USP). Instituto de Matemática e Estatística (IME/SBI) |
| Defense date: | 2014-04-16 |
| Examining board members: |
Ernesto Julian Goldberg Birgin;
José Mario Martinez Perez;
Sandra Augusta Santos
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| Advisor: | Ernesto Julian Goldberg Birgin |
| Abstract | |
In this work, we propose an interior-point method for large-scale linearly constrained optimization. This method explores the linearity of the constraints, starting from a feasible point and preserving the feasibility of the iterates. We present the main global convergence results, together with a rich description of the implementation details of all the steps of the method. To validate the implementation of the method, we present a wide set of numerical experiments and a comparative analysis with well known softwares of the continuous optimization community. (AU) | |
| FAPESP's process: | 12/05725-0 - Implementation of a software for large-scale minimization with linear constraints using trust-region methods |
| Grantee: | John Lenon Cardoso Gardenghi |
| Support Opportunities: | Scholarships in Brazil - Master |