A Distributed Optimization Problem Subject to Partial-Impact Cost Functions
研究了一个受部分影响成本函数约束的分布式优化问题，提出了两种算法（结构式和梯度式），并用非光滑分析和坐标变换定理建立了算法平衡点与优化问题之间的联系，最后通过两个数值例子验证了算法的有效性。
This article focuses on a distributed optimization problem subject to partial-impact cost functions that relates to two decision variable vectors. To this end, two algorithms are presented with the aim of solving the considered optimization problem in a structure fashion and in a gradient fashion, respectively. Furthermore, a connection between the equilibrium of the induced algorithm and the involved optimization problem is established, with the aid of the tools from nonsmooth analysis and change of coordinate theorem. Two numerical examples with practical significance are given to demonstrate the efficiency of the designed algorithm.