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A distributed algorithm for solving quadratic optimization problems
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DOI：10.1016/j.compchemeng.2024.108778.png)
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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.
Keyword:
Distributed optimization
Duality
Multi-agent systems
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C
IF:
3.9
论文数:
8.1K
被引数:
1.7W
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