### Abstract

We consider a multi-agent convex optimization problem where the agents are to minimize a sum of local objective functions subject to a global inequality constraint, a global equality constraint and a global constraint set. We devise a distributed primal-dual subgradient algorithm which is based on the characterization of the primal-dual optimal solutions as the saddle points of the penalty function. This algorithm allows the agents exchange information over networks with time-varying topologies and asymptotically agree on an optimal solution and the optimal value.

Original language | English (US) |
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Title of host publication | Proceedings of the 2010 American Control Conference, ACC 2010 |

Pages | 2434-2439 |

Number of pages | 6 |

State | Published - Oct 15 2010 |

Event | 2010 American Control Conference, ACC 2010 - Baltimore, MD, United States Duration: Jun 30 2010 → Jul 2 2010 |

### Publication series

Name | Proceedings of the 2010 American Control Conference, ACC 2010 |
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### Other

Other | 2010 American Control Conference, ACC 2010 |
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Country | United States |

City | Baltimore, MD |

Period | 6/30/10 → 7/2/10 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Control and Systems Engineering

### Cite this

*Proceedings of the 2010 American Control Conference, ACC 2010*(pp. 2434-2439). [5530577] (Proceedings of the 2010 American Control Conference, ACC 2010).

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*Proceedings of the 2010 American Control Conference, ACC 2010.*, 5530577, Proceedings of the 2010 American Control Conference, ACC 2010, pp. 2434-2439, 2010 American Control Conference, ACC 2010, Baltimore, MD, United States, 6/30/10.

**On distributed optimization under inequality and equality constraints via penalty primal-dual methods.** / Zhu, Minghui; Martínez, Sonia.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - On distributed optimization under inequality and equality constraints via penalty primal-dual methods

AU - Zhu, Minghui

AU - Martínez, Sonia

PY - 2010/10/15

Y1 - 2010/10/15

N2 - We consider a multi-agent convex optimization problem where the agents are to minimize a sum of local objective functions subject to a global inequality constraint, a global equality constraint and a global constraint set. We devise a distributed primal-dual subgradient algorithm which is based on the characterization of the primal-dual optimal solutions as the saddle points of the penalty function. This algorithm allows the agents exchange information over networks with time-varying topologies and asymptotically agree on an optimal solution and the optimal value.

AB - We consider a multi-agent convex optimization problem where the agents are to minimize a sum of local objective functions subject to a global inequality constraint, a global equality constraint and a global constraint set. We devise a distributed primal-dual subgradient algorithm which is based on the characterization of the primal-dual optimal solutions as the saddle points of the penalty function. This algorithm allows the agents exchange information over networks with time-varying topologies and asymptotically agree on an optimal solution and the optimal value.

UR - http://www.scopus.com/inward/record.url?scp=77957791600&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77957791600&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:77957791600

SN - 9781424474264

T3 - Proceedings of the 2010 American Control Conference, ACC 2010

SP - 2434

EP - 2439

BT - Proceedings of the 2010 American Control Conference, ACC 2010

ER -