| Grant number: | 21/14011-0 |
| Support Opportunities: | Regular Research Grants |
| Start date: | May 01, 2022 |
| End date: | April 30, 2024 |
| Field of knowledge: | Physical Sciences and Mathematics - Mathematics - Applied Mathematics |
| Principal Investigator: | Luis Felipe Cesar da Rocha Bueno |
| Grantee: | Luis Felipe Cesar da Rocha Bueno |
| Host Institution: | Instituto de Ciência e Tecnologia (ICT). Universidade Federal de São Paulo (UNIFESP). Campus São José dos Campos. São José dos Campos , SP, Brazil |
Abstract
In this project, we present some research alternatives related to Inexact Restoration methods so that it is possible to use them efficiently to address some interesting applications. We propose to do a modular presentation of the algorithms so that any modification alternative can be made without the entire theory needing to be revised. In this way, we believe that several acceleration elements can be considered for each specific problem to be solved. With this philosophy, we intend to deal with problems arising from Data Science and Structural Optimization. In the first case, we hope to solve constrained optimization problems, in which is convenient the imprecise evaluation of the functions that define it. For this, we will use an artificial variable and an artificial constraint to control the level of precision in evaluating the functions involved and treat them in an Inexact Restoration scheme. For Structural Optimization, we intend to present a globalization of a Sequential Linear Programming method using the developed Inexact Restoration theory and allowing specific accelerations with respect to the problem of interest. (AU)
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