A distributed algorithm for solving quadratic optimization problems

被引：0

作者：

Jahvani, Mohammad ^{[1
]}

Guay, Martin ^{[1
]}

机构：

[1] Queens Univ, Dept Chem Engn, 19 Div St, Kingston, ON K7L 3N6, Canada

来源：

COMPUTERS & CHEMICAL ENGINEERING | 2024年 / 189卷

关键词：

Distributed optimization; Duality; Multi-agent systems; CONVEX-OPTIMIZATION; CONSENSUS; FLOW;

D O I：

10.1016/j.compchemeng.2024.108778

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Unconstrained quadratic optimization problems are a common mathematical challenge encountered in various domains. These problems involve optimizing quadratic functions without explicit constraints. In a distributed computing environment, solving these optimization problems collectively among multiple computational nodes is a complex and crucial task. This paper introduces a distributed algorithm within a multi-agent framework that aims to find the global minimizer for such problems. The proposed algorithm demonstrates exponential convergence, assuming a static and connected communication network. Additionally, numerical simulations are conducted to support the theoretical findings.

引用

页数：7

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