The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
A control perspective for centralized and distributed convex optimization
Abstract
In this paper, we want to study how natural and engineered systems could perform complex optimizations with limited computational and communication capabilities. We adopt a continuous-time dynamical system view rooted in early work on optimization and more recently in network protocol design, and merge it with the dynamic view of distributed averaging systems. We obtain a general approach, based on the control system viewpoint, that allows to analyze and design (distributed) optimization systems converging to the solution of given convex optimization problems. The control system viewpoint provides many insights and new directions of research. We apply the framework to a distributed optimal location problem and demonstrate the natural tracking and adaptation capabilities of the system to changing constraints.
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. (2011) · Foundations and Trends® in Machine Learning · doi:10.1561/2200000016 · Cited by 17,075
Consensus Problems in Networks of Agents With Switching Topology and Time-Delays
Olfati-Saber, R., & Murray, R. M. (2004) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2004.834113 · Cited by 12,788
Distributed Subgradient Methods for Multi-Agent Optimization
Nedic, A., & Ozdaglar, A. (2009) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2008.2009515 · Cited by 3,719
Distributed Stochastic Subgradient Projection Algorithms for Convex Optimization
Sundhar Ram, S., Nedić, A., & Veeravalli, V. V. (2010) · Journal of Optimization Theory and Applications · doi:10.1007/s10957-010-9737-7 · Cited by 814
Distributed multi-agent optimization with state-dependent communication
Lobel, I., Ozdaglar, A., & Feijer, D. (2011) · Mathematical Programming · doi:10.1007/s10107-011-0467-x · Cited by 162
Cited by
Yi, P., Hong, Y., & Liu, F. (2016) · Automatica · doi:10.1016/j.automatica.2016.08.007 · Cited by 478
Xu, J., Zhu, S., Soh, Y. C., & Xie, L. (2015) · 2015 54th IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2015.7402509 · Cited by 332
Linear Convergence Rate of a Class of Distributed Augmented Lagrangian Algorithms
Jakovetic, D., Moura, J. M. F., & Xavier, J. (2015) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2014.2363299 · Cited by 123
Continuous-time distributed convex optimization on weight-balanced digraphs
Gharesifard, B., & Cortes, J. (2012) · 2012 IEEE 51st IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2012.6426897 · Cited by 32
Augmented distributed optimization for networked systems
Xu, J. (2019) · doi:10.32657/10356/68805 · Cited by 5
Metadata
- Authors
- Wang, J., & Elia, N.
- Venue
- IEEE Conference on Decision and Control and European Control Conference
- Publisher
- IEEE
- Published
- 2011-12
- Pages
- 3800-3805
- OpenAlex
- W2070291355
- Cited by
- 398
- References
- 6
- FWCI
- 10.57
- Type
- conference paper
- Language
- en
- Open access
- closed
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