An inexact restoration approach to optimization problems with multiobjective constraints under weighted-sum scalarization
Bueno, L. F. [UNIFESP]
Martinez, J. M.
Is part ofOptimization Letters
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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.
CitationOptimization Letters. Heidelberg, v. 10, n. 6, p. 1315-1325, 2016.
CEPID-Cemeai-Fapesp Industrial Mathematics
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