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Article Dans Une Revue Computational Optimization and Applications Année : 2023

A subgradient method with non-monotone line search

Résumé

In this paper we present a subgradient method with non-monotone line search for the minimization of convex functions with simple convex constraints. Different from the standard subgradient method with prefixed step sizes, the new method selects the step sizes in an adaptive way. Under mild conditions asymptotic convergence results and iteration-complexity bounds are obtained. Preliminary numerical results illustrate the relative efficiency of the proposed method.
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Dates et versions

hal-03880925 , version 1 (01-12-2022)

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O P Ferreira, G N Grapiglia, E M Santos, J C O Souza. A subgradient method with non-monotone line search. Computational Optimization and Applications, 2023, 84 (2), pp.397-420. ⟨10.1007/s10589-022-00438-z⟩. ⟨hal-03880925⟩
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