Global Optimization: A Distributed Compensation Algorithm and its Convergence Analysis

Wen-Ting Lin; Yan-Wu Wang; Chaojie Li; Jiang-Wen Xiao

doi:10.1109/TSMC.2019.2912825

Global Optimization: A Distributed Compensation Algorithm and its Convergence Analysis

Wen-Ting Lin
, Yan-Wu Wang^*
, Chaojie Li
, Jiang-Wen Xiao

^*Corresponding author for this work

Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

7 Citations (Scopus)

Abstract

This paper introduces a distributed compensation approach for the global optimization with separable objective functions and coupled constraints. By employing compensation variables, the global optimization problem can be solved without the information exchange of coupled constraints. The convergence analysis of the proposed algorithm is presented with the convergence condition through which a diminishing step-size with an upper bound can be determined. The convergence rate can be achieved at O(lnT√T). Moreover, the equilibrium of this algorithm is proved to converge at the optimal solution of the global optimization problem. The effectiveness and the practicability of the proposed algorithm is demonstrated by the parameter optimization problem in smart building. © 2013 IEEE.

Original language	English
Article number	8708976
Pages (from-to)	2355-2369
Number of pages	15
Journal	IEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume	51
Issue number	4
Online published	7 May 2019
DOIs	https://doi.org/10.1109/TSMC.2019.2912825
Publication status	Published - Apr 2021
Externally published	Yes

Funding

This work was supported in part by the National Natural Science Foundation of China under Grant 61773172, Grant 61572210, and Grant 51537003, in part by the Natural Science Foundation of Hubei Province of China under Grant 2017CFA035, and in part by the Academic Frontier Youth Team of HUST.

Research Keywords

Compensation approach
coupled constraints
distributed optimization
global optimal

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title = "Global Optimization: A Distributed Compensation Algorithm and its Convergence Analysis",

abstract = "This paper introduces a distributed compensation approach for the global optimization with separable objective functions and coupled constraints. By employing compensation variables, the global optimization problem can be solved without the information exchange of coupled constraints. The convergence analysis of the proposed algorithm is presented with the convergence condition through which a diminishing step-size with an upper bound can be determined. The convergence rate can be achieved at O(lnT√T). Moreover, the equilibrium of this algorithm is proved to converge at the optimal solution of the global optimization problem. The effectiveness and the practicability of the proposed algorithm is demonstrated by the parameter optimization problem in smart building. {\textcopyright} 2013 IEEE.",

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author = "Wen-Ting Lin and Yan-Wu Wang and Chaojie Li and Jiang-Wen Xiao",

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T1 - Global Optimization

T2 - A Distributed Compensation Algorithm and its Convergence Analysis

AU - Lin, Wen-Ting

AU - Wang, Yan-Wu

AU - Li, Chaojie

AU - Xiao, Jiang-Wen

PY - 2021/4

Y1 - 2021/4

N2 - This paper introduces a distributed compensation approach for the global optimization with separable objective functions and coupled constraints. By employing compensation variables, the global optimization problem can be solved without the information exchange of coupled constraints. The convergence analysis of the proposed algorithm is presented with the convergence condition through which a diminishing step-size with an upper bound can be determined. The convergence rate can be achieved at O(lnT√T). Moreover, the equilibrium of this algorithm is proved to converge at the optimal solution of the global optimization problem. The effectiveness and the practicability of the proposed algorithm is demonstrated by the parameter optimization problem in smart building. © 2013 IEEE.

AB - This paper introduces a distributed compensation approach for the global optimization with separable objective functions and coupled constraints. By employing compensation variables, the global optimization problem can be solved without the information exchange of coupled constraints. The convergence analysis of the proposed algorithm is presented with the convergence condition through which a diminishing step-size with an upper bound can be determined. The convergence rate can be achieved at O(lnT√T). Moreover, the equilibrium of this algorithm is proved to converge at the optimal solution of the global optimization problem. The effectiveness and the practicability of the proposed algorithm is demonstrated by the parameter optimization problem in smart building. © 2013 IEEE.

KW - Compensation approach

KW - coupled constraints

KW - distributed optimization

KW - global optimal

UR - https://www.scopus.com/pages/publications/85103188603

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U2 - 10.1109/TSMC.2019.2912825

DO - 10.1109/TSMC.2019.2912825

M3 - RGC 21 - Publication in refereed journal

SN - 2168-2216

VL - 51

SP - 2355

EP - 2369

JO - IEEE Transactions on Systems, Man, and Cybernetics: Systems

JF - IEEE Transactions on Systems, Man, and Cybernetics: Systems

IS - 4

M1 - 8708976

ER -

Global Optimization: A Distributed Compensation Algorithm and its Convergence Analysis

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