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Distributed Convex Optimization with Inequality Constraints over Time-Varying Unbalanced Digraphs

机译:时变不平衡有向图不等式约束的分布式凸优化

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This paper considers a distributed convex optimization problem with inequality constraints over time-varying unbalanced digraphs, where the cost function is a sum of local objective functions, and each node of the graph only knows its local objective and inequality constraints. Although there is a vast body of literature on distributed optimization, most of them require the graph to be balanced, which is quite restrictive and not necessary. To solve it, this work proposes a novel idea of using the epigraph form of the constrained optimization, which can be easily used to study time-varying unbalanced digraphs. Under local communications, a simple iterative algorithm is then designed for each node. We prove that if the graph is uniformly jointly strongly connected, each node asymptotically converges to some common optimal solution.
机译:本文考虑时变不平衡有向图上具有不等式约束的分布凸优化问题,其中成本函数是局部目标函数的总和,图的每个节点仅知道其局部目标和不等式约束。尽管有大量关于分布式优化的文献,但是大多数文献都要求图是平衡的,这是非常严格的,没有必要。为了解决这个问题,这项工作提出了一种使用约束优化的题词形式的新颖想法,可以很容易地用于研究时变不平衡图。在本地通信下,然后为每个节点设计一个简单的迭代算法。我们证明,如果图是统一联合强连接的,则每个节点渐近收敛到某个常见的最优解。

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