Optimization of Buffer Networks via DC Programming

This brief is concerned with the <inline-formula> <tex-math notation="LaTeX">H^{2} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">H^{\infty } </tex-math></inline-formula> norm-constrained optimization p...

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Bibliographic Details
Published in:IEEE Transactions on Circuits and Systems II: Express Briefs Vol. 70; no. 2; pp. 606 - 610
Main Authors: Zhao, Chengyan, Sakurama, Kazunori, Ogura, Masaki
Format: Journal Article
Language:English
Published: New York IEEE 01.02.2023
Institute of Electrical and Electronics Engineers (IEEE)
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
buffer network
Buffers
car-sharing service
Convexity
DC programming
H² norm
H∞ norm
Linear systems
Mathematical models
Networks
nonconvex optimization
Optimization
Positive linear system
posynomial
Pricing
Programming
Vehicle dynamics
ISSN:1549-7747, 1558-3791
Online Access:Get full text
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Summary:This brief is concerned with the <inline-formula> <tex-math notation="LaTeX">H^{2} </tex-math></inline-formula> and <inline-formula> <tex-math notation="LaTeX">H^{\infty } </tex-math></inline-formula> norm-constrained optimization problems of dynamic buffer networks. The extended network model is introduced first, wherein the weights of all edges can be tuned independently. Because of the emerging nonconvexity of the extended model, previous results of positive linear systems failed to address this situation. By resorting to the log-log convexity of a class of nonlinear functions called posynomials, the optimization problems can be reduced to differential convex programming problems. The proposed framework is illustrated for large-scale networks.
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ISSN:1549-7747
1558-3791
DOI:10.1109/TCSII.2022.3212693