Multiuser Optimization: Distributed Algorithms and Error Analysis
Multiuser Optimization: Distributed Algorithms and Error Analysis
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DOI：
10.1137/090770102
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发表时间：
2011-09
期刊：
影响因子：
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通讯作者：
Jayash Koshal;A. Nedić;U. Shanbhag
中科院分区：
文献类型：
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作者：
Jayash Koshal;A. Nedić;U. Shanbhag
传统上，多用户问题是一个约束优化问题，其特征在于一组用户，由用户特定的效用函数的总和给定的目标，以及耦合用户决策的线性约束的集合。用户不共享关于他们的实用程序的信息，但是交流他们的决策变量的值。多用户问题是在满足用户信息需求的前提下，最大化用户效用函数之和。在本文中，我们专注于推广凸多用户优化问题的目标和约束是不可分离的用户，而不是考虑用户的决策耦合的情况下，无论是在目标和通过非线性耦合约束。为了解决这个问题，我们考虑应用基于梯度的分布式算法的近似的多用户问题。这样的近似是通过吉洪诺夫regulariza.
Traditionally, a multiuser problem is a constrained optimization problem characterized by a set of users, an objective given by a sum of user-specific utility functions, and a collection of linear constraints that couple the user decisions. The users do not share the information about their utilities, but do communicate values of their decision variables. The multiuser problem is to maximize the sum of the user-specific utility functions subject to the coupling constraints, while abiding by the informational requirements of each user. In this paper, we focus on generalizations of convex multiuser optimization problems where the objective and constraints are not separable by user and instead consider instances where user decisions are coupled, both in the objective and through nonlinear coupling constraints. To solve this problem, we consider the application of gradient-based distributed algorithms on an approximation of the multiuser problem. Such an approximation is obtained through a Tikhonov regulariza...