A primal-dual method for conic constrained distributed optimization problems
A primal-dual method for conic constrained distributed optimization problems
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发表时间：
2016-07
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通讯作者：
N. Aybat;E. Y. Hamedani
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作者：
N. Aybat;E. Y. Hamedani
我们考虑合作多智能体共识优化问题的无向网络的代理，只有那些代理连接的边缘可以直接沟通。我们的目标是最小化代理特定的复合凸函数在代理特定的私人圆锥约束集的总和，因此，最佳的共识决策应该在于这些私人集的交集。我们提供了次最优、不可行和违反共识的收敛率;检查底层网络拓扑对所提出的分散算法收敛率的影响;并展示如何扩展这些方法来处理时变通信网络并解决问题资源共享约束。
We consider cooperative multi-agent consensus optimization problems over an undirected network of agents, where only those agents connected by an edge can directly communicate. The objective is to minimize the sum of agent-specific composite convex functions over agent-specific private conic constraint sets; hence, the optimal consensus decision should lie in the intersection of these private sets. We provide convergence rates both in sub-optimality, infeasibility and consensus violation; examine the effect of underlying network topology on the convergence rates of the proposed decentralized algorithms; and show how to extend these methods to handle time-varying communications networks and to solve problems with resource sharing constraints.