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- W2117397310 abstract "One way to solve large-scale linear programming problems is to exploit the Lagrangian relaxation of the difficult constraints and use subgradient methods. Such methods are popular as they give good approximations of dual solutions. Unfortunately, they do not directly yield primal solutions. Two alternatives to obtain primal solutions under reasonable computational cost are the construction of ergodic sequences and the use of the recently developed volume algorithm. While the convergence of ergodic sequences is well understood, the convergence properties of the volume algorithm is not well established in the original paper. This lead to some modifications of the original method to ease the proof of dual convergence. Three alternatives are the revised volume algorithm, a special case of the bundle method, and the volume algorithm incorporated by the variable target value method. The aim of this work is to study such algorithms and all related concepts, especially convex analysis and nondifferentiable optimization. We analysed the main theoretical differences among the methods and performed numerical experiments with linear and integer problems, in particular, the maximum cut problem on graphs." @default.
- W2117397310 created "2016-06-24" @default.
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- W2117397310 date "2015-10-21" @default.
- W2117397310 modified "2023-09-24" @default.
- W2117397310 title "Algoritmo do volume e otimização não diferenciável" @default.
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- W2117397310 doi "https://doi.org/10.11606/d.45.2007.tde-04062007-115956" @default.
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