CLC number: O224
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2023-02-02
Cited: 0
Clicked: 1503
Qian XU, Chutian YU, Xiang YUAN, Mengli WEI, Hongzhe LIU. Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid[J]. Frontiers of Information Technology & Electronic Engineering, 2023, 24(9): 1253-1260.
@article{title="Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid",
author="Qian XU, Chutian YU, Xiang YUAN, Mengli WEI, Hongzhe LIU",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="24",
number="9",
pages="1253-1260",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2200596"
}
%0 Journal Article
%T Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid
%A Qian XU
%A Chutian YU
%A Xiang YUAN
%A Mengli WEI
%A Hongzhe LIU
%J Frontiers of Information Technology & Electronic Engineering
%V 24
%N 9
%P 1253-1260
%@ 2095-9184
%D 2023
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2200596
TY - JOUR
T1 - Distributed optimization based on improved push-sum framework for optimization problem with multiple local constraints and its application in smart grid
A1 - Qian XU
A1 - Chutian YU
A1 - Xiang YUAN
A1 - Mengli WEI
A1 - Hongzhe LIU
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 24
IS - 9
SP - 1253
EP - 1260
%@ 2095-9184
Y1 - 2023
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2200596
Abstract: In this paper, the optimization problem subject to N nonidentical closed convex set constraints is studied. The aim is to design a corresponding distributed optimization algorithm over the fixed unbalanced graph to solve the considered problem. To this end, with the push-sum framework improved, the distributed optimization algorithm is newly designed, and its strict convergence analysis is given under the assumption that the involved graph is strongly connected. Finally, simulation results support the good performance of the proposed algorithm.
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