Composite optimization for the resource allocation problem

被引:7
|
作者
Ivanova, Anastasiya [1 ,2 ]
Dvurechensky, Pavel [3 ,4 ]
Gasnikov, Alexander [1 ,2 ,4 ]
Kamzolov, Dmitry [1 ]
机构
[1] Moscow Inst Phys & Technol, Moscow, Russia
[2] Natl Res Univ Higher Sch Econ, Moscow, Russia
[3] Weierstrass Inst Appl Anal & Stochast, Berlin, Germany
[4] RAS, Inst Informat Transmiss Problems, Moscow, Russia
来源
OPTIMIZATION METHODS & SOFTWARE | 2021年 / 36卷 / 04期
基金
俄罗斯基础研究基金会;
关键词
Decentralized pricing; primal-dual method; accelerated gradient method; gradient method; composite optimization; CONVEX; MINIMIZATION; ALGORITHMS; DESCENT; SMOOTH;
D O I
10.1080/10556788.2020.1712599
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In this paper, we consider resource allocation problem stated as a convex minimization problem with linear constraints. To solve this problem, we use gradient and accelerated gradient descent applied to the dual problem and prove the convergence rate both for the primal iterates and the dual iterates. We obtain faster convergence rates than the ones known in the literature. We also provide economic interpretation for these two methods. This means that iterations of the algorithms naturally correspond to the process of price and production adjustment in order to obtain the desired production volume in the economy. Overall, we show how these actions of the economic agents lead the whole system to the equilibrium.
引用
收藏
页码:720 / 754
页数:35
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