A generalized conditional gradient method for multiobjective composite optimization problems
This article deals with multiobjective composite optimization problems that consist of simultaneously minimizing several objective functions, each of which is composed of a combination of smooth and non-smooth functions. To tackle these problems, we propose a generalized version of the conditional g...
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Main Authors | , , |
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Format | Journal Article |
Language | English |
Published |
24.02.2023
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Subjects | |
Online Access | Get full text |
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Summary: | This article deals with multiobjective composite optimization problems that
consist of simultaneously minimizing several objective functions, each of which
is composed of a combination of smooth and non-smooth functions. To tackle
these problems, we propose a generalized version of the conditional gradient
method, also known as Frank-Wolfe method. The method is analyzed with three
step size strategies, including Armijo-type, adaptive, and diminishing step
sizes. We establish asymptotic convergence properties and iteration-complexity
bounds, with and without convexity assumptions on the objective functions.
Numerical experiments illustrating the practical behavior of the methods are
presented. |
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DOI: | 10.48550/arxiv.2302.12912 |