An online dual consensus algorithm for distributed resource allocation over networks

被引：0
|
作者：
Chen, Yuwei [1 ]
Deng, Zengde [1 ]
Yuan, Biao [4 ]
Chen, Zaiyi [1 ]
Chen, Yujie [2 ]
Hu, Haoyuan [3 ]
机构：
[1] Cainiao Network, Hangzhou, Zhejiang, Peoples R China
[2] Cainiao Network, Applicat Algorithm Design & Dev, Hangzhou, Zhejiang, Peoples R China
[3] Cainiao Network, Artificial Intelligence Dept, Hangzhou, Zhejiang, Peoples R China
[4] Shanghai Jiao Tong Univ, Sino US Global Logist Inst, Data Driven Management Decis Making Lab, Shanghai, Peoples R China
来源：
IISE TRANSACTIONS | 2024年
基金：
中国国家自然科学基金;
关键词：
Distributed decision-making; online optimization; resource allocation; ADMM; OPTIMIZATION;
D O I：
10.1080/24725854.2024.2428652
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
We address the problem of online resource allocation in a distributed environment where requests arrive dynamically over time at different agents in the network. As each request arrives, the receiving agent must make an immediate decision that incurs a cost and consumes a certain amount of resources. The requests are drawn independently from unknown distributions that are different for each agent. First, we present an Online Consensus Alternating Direction Method of Multipliers (OC-ADMM) algorithm for the dual counterpart of the online distributed resource allocation problem, focusing on the dual variables. Then, we propose an Online Dual Consensus ADMM (ODC-ADMM) algorithm for the primal problem to derive the primal variables from the dual update process in the OC-ADMM algorithm. The ODC-ADMM algorithm exhibits sublinear growth in both regret and expected constraint violation with respect to the time horizon. Furthermore, extensive numerical results on both synthetic and real-world data confirm its effectiveness.
引用
收藏
页数：12
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