This paper considers a second-order multi-agent system for solving the non-smooth convex optimization problem, where the global objective function is a sum of local convex objective functions within different bound constraints over undirected graphs. A novel distributed continuous-time optimization algorithm is designed, where each agent only has an access to its own objective function and bound constraint. All the agents cooperatively minimize the global objective function under some mild conditions. In virtue of the KKT condition and the Lagrange multiplier method, the convergence of the resultant dynamical system is ensured by involving the Lyapunov stability theory and the hybrid LaSalle invariance principle of differential inclusion. A numerical example is conducted to verify the theoretical results.
Published in | Applied and Computational Mathematics (Volume 5, Issue 3) |
DOI | 10.11648/j.acm.20160503.14 |
Page(s) | 114-120 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2016. Published by Science Publishing Group |
Distributed Optimization, Multi-Agent Network, Lyapunov Method, Bound Constraint, Continuous-Time
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APA Style
Ping Liu, Huaqing Li, Liping Feng. (2016). A Continuous-Time Multi-Agent Systems Based Algorithm for Constrained Distributed Optimization. Applied and Computational Mathematics, 5(3), 114-120. https://doi.org/10.11648/j.acm.20160503.14
ACS Style
Ping Liu; Huaqing Li; Liping Feng. A Continuous-Time Multi-Agent Systems Based Algorithm for Constrained Distributed Optimization. Appl. Comput. Math. 2016, 5(3), 114-120. doi: 10.11648/j.acm.20160503.14
AMA Style
Ping Liu, Huaqing Li, Liping Feng. A Continuous-Time Multi-Agent Systems Based Algorithm for Constrained Distributed Optimization. Appl Comput Math. 2016;5(3):114-120. doi: 10.11648/j.acm.20160503.14
@article{10.11648/j.acm.20160503.14, author = {Ping Liu and Huaqing Li and Liping Feng}, title = {A Continuous-Time Multi-Agent Systems Based Algorithm for Constrained Distributed Optimization}, journal = {Applied and Computational Mathematics}, volume = {5}, number = {3}, pages = {114-120}, doi = {10.11648/j.acm.20160503.14}, url = {https://doi.org/10.11648/j.acm.20160503.14}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.acm.20160503.14}, abstract = {This paper considers a second-order multi-agent system for solving the non-smooth convex optimization problem, where the global objective function is a sum of local convex objective functions within different bound constraints over undirected graphs. A novel distributed continuous-time optimization algorithm is designed, where each agent only has an access to its own objective function and bound constraint. All the agents cooperatively minimize the global objective function under some mild conditions. In virtue of the KKT condition and the Lagrange multiplier method, the convergence of the resultant dynamical system is ensured by involving the Lyapunov stability theory and the hybrid LaSalle invariance principle of differential inclusion. A numerical example is conducted to verify the theoretical results.}, year = {2016} }
TY - JOUR T1 - A Continuous-Time Multi-Agent Systems Based Algorithm for Constrained Distributed Optimization AU - Ping Liu AU - Huaqing Li AU - Liping Feng Y1 - 2016/06/18 PY - 2016 N1 - https://doi.org/10.11648/j.acm.20160503.14 DO - 10.11648/j.acm.20160503.14 T2 - Applied and Computational Mathematics JF - Applied and Computational Mathematics JO - Applied and Computational Mathematics SP - 114 EP - 120 PB - Science Publishing Group SN - 2328-5613 UR - https://doi.org/10.11648/j.acm.20160503.14 AB - This paper considers a second-order multi-agent system for solving the non-smooth convex optimization problem, where the global objective function is a sum of local convex objective functions within different bound constraints over undirected graphs. A novel distributed continuous-time optimization algorithm is designed, where each agent only has an access to its own objective function and bound constraint. All the agents cooperatively minimize the global objective function under some mild conditions. In virtue of the KKT condition and the Lagrange multiplier method, the convergence of the resultant dynamical system is ensured by involving the Lyapunov stability theory and the hybrid LaSalle invariance principle of differential inclusion. A numerical example is conducted to verify the theoretical results. VL - 5 IS - 3 ER -