An inexact restoration approach to optimization problems with multiobjective constraints under weighted-sum scalarization

Author(s)

Bueno, L. F. ; Haeser, G. ; Martinez, J. M.

• Document type: Journal article
• Source: Optimization Letters; v. 10, n. 6, p. 1315-1325, AUG 2016.
• Web of Science Citations: 3

Abstract

We apply a flexible inexact-restoration (IR) algorithm to optimization problems with multiobjective constraints under the weighted-sum scalarization approach. In IR methods each iteration has two phases. In the first phase one aims to improve the feasibility and, in the second phase, one minimizes a suitable objective function. We show that with the IR framework there is a natural way to explore the structure of the problem in both IR phases. Numerical experiments are conducted on Portfolio optimization, the More-Garbow-Hillstrom collection, and random fourth-degree polynomials, where we show the advantages of exploiting the structure of the problem. (AU)

• FAPESP's process: 14/01446-5 - SIAM conference on optimization
• Grantee: Luis Felipe Cesar da Rocha Bueno
• Support Opportunities: Research Grants - Meeting - Abroad
• FAPESP's process: 13/05475-7 - Computational methods in optimization
• Grantee: Sandra Augusta Santos
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 15/02528-8 - Newton-type methods for linear and nonlinear optimization
• Grantee: Luis Felipe Cesar da Rocha Bueno
• Support Opportunities: Regular Research Grants
• FAPESP's process: 10/19720-5 - Optimality conditions and inexact restoration
• Grantee: Gabriel Haeser
• Support Opportunities: Research Grants - Young Investigators Grants