Dual subgradient method with averaging for optimal resource allocation

Yurii Nesterov () and Vladimir Shikhman ()
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Yurii Nesterov: Université catholique de Louvain, CORE, Belgium
Vladimir Shikhman: Université catholique de Louvain, CORE, Belgium

No 2017013, LIDAM Discussion Papers CORE from Université catholique de Louvain, Center for Operations Research and Econometrics (CORE)

Abstract: A dual subgradient method is proposed for solving convex optimization problems with linear constraints. As novelty, the recovering of primal solutions can be avoided. Instead, the optimal convergence rate for the whole sequence of primal-dual iterates is obtained. This is due to the primal-dual averaging strategies which are incorporated into the itera-tive scheme. We apply our dual subgradient method with averaging to optimal resource allocation within a multi-agent environment. The proposed dual subgradient method nat-urally corresponds to a distributed process of production/price adjustments and e ectively leads to a market equilibrium.

Keywords: convex programming; dual subgradient methods; rate of conver-gence; averaging; resource allocation (search for similar items in EconPapers)
Date: 2017-04-21
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