基于惩罚法求解局部不等式约束下的指定时间分布式优化问题

Yu-quan Zhang, Chengxin Xian, Yu Zhao
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引用次数: 0

摘要

本文主要研究无向图上具有局部非线性不等式约束的给定时间内的分布式优化问题。本文提出了一种具有指定时间的分布式优化算法。它可以用于多智能体网络,以最小化局部目标函数的和。该算法中指定时间的建立不依赖于初始条件和算法参数。这是一个完全分布式的算法,只需要相邻agent之间的信息交互就可以完成指定时间的优化问题。通过一个资源分配实例验证了该理论的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Solving specified-time distributed optimization problem with local inequality constraint based on penalty method
This paper focuses on solving distributed optimization problems with local nonlinear inequality constraints in a specified-time over undirected graph. Here, we present a distributed optimization algorithm with specified-time. It can be used for the multi-agent network to minimize the sum of local objective functions. The establishment of specified-time in the proposed algorithm is independent of initial conditions and algorithm parameters. This is a completely distributed algorithm, which only needs information interaction between adjacent agents to complete the specified-time optimization problem. The effectiveness of the proposed theory is demonstrated by an example of resource allocation.
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