Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/142714
Title: A dual splitting approach for distributed resource allocation with regularization
Authors: Xu, Jinming
Zhu, Shanying
Soh, Yeng Chai
Xie, Lihua
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Xu, J., Zhu, S., Soh, Y. C., & Xie, L. (2019). A dual splitting approach for distributed resource allocation with regularization. IEEE Transactions on Control of Network Systems, 6(1), 403-414. doi:10.1109/TCNS.2018.2834310
Journal: IEEE Transactions on Control of Network Systems
Abstract: We deal with a class of distributed resource allocation problems where each agent attempts to minimize its own cost while respecting network-wide resource constraints as well as local capacity limits. This problem arises from many areas, such as economic dispatch, network utility maximization, and demand response. Most existing methods are centralized while few works are devoted to solving the problem in a distributed manner. The problem becomes even more challenging when there is a (nonsmooth) regularization term in the cost function. In this paper, we propose a novel distributed algorithm (termed DuSPA) to solve the above problem based on duality analysis and splitting methods. For privacy concerns, this algorithm is not required to communicate sensitive gradient information while still achieving the optimum without sacrificing the performance. We will show that the proposed algorithm converges at a nonergodic convergence rate of O(1/k) for general convex cost functions and a linear convergence rate for smooth and strongly convex cost functions, respectively. Furthermore, we apply the proposed algorithm to an economic dispatch problem to show its effectiveness.
URI: https://hdl.handle.net/10356/142714
ISSN: 2372-2533
DOI: 10.1109/TCNS.2018.2834310
Rights: © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TCNS.2018.2834310.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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