论文标题
预计的推送梯度下降，用于凸优化，以适用于经济调度问题
Projected Push-Sum Gradient Descent-Ascent for Convex Optimizationwith Application to Economic Dispatch Problems
论文作者
论文摘要
我们提出了一种用于求解凸，约束和分布的优化问题定义在多代理网络上的新算法，在该算法中，每个代理都可以独家访问全局目标函数的一部分。代理人能够通过有向的加权通信图交换信息，该图形可以表示为柱状矩阵。该算法结合了调整后的推送和共识协议，以进行信息扩散和对局部成本函数的梯度下降，从而使收敛至最佳的总和。考虑到分布式优化中的标准假设，我们将推动和重新印度重新重新制定为单个矩阵上升。该算法应用于分布式的经济调度问题，其中约束可以在本地和全球子集中表达。
We propose a novel algorithm for solving convex, constrained and distributed optimization problems defined on multi-agent-networks, where each agent has exclusive access to a part of the global objective function. The agents are able to exchange information over a directed, weighted communication graph, which can be represented as a column-stochastic matrix. The algorithm combines an adjusted push-sum consensus protocol for information diffusion and a gradient descent-ascent on the local cost functions, providing convergence to the optimum of their sum. We provide results on a reformulation of the push-sum into single matrix-updates and prove convergence of the proposed algorithm to an optimal solution, given standard assumptions in distributed optimization. The algorithm is applied to a distributed economic dispatch problem, in which the constraints can be expressed in local and global subsets.
