On Distributed Convex Optimization Under Inequality and Equality Constraints

We consider a general multi-agent convex optimization problem where the agents are to collectively minimize a global objective function subject to a global inequality constraint, a global equality constraint, and a global constraint set. The objective function is defined by a sum of local objective...

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Veröffentlicht in:	IEEE transactions on automatic control Jg. 57; H. 1; S. 151 - 164
Hauptverfasser:	Minghui Zhu, Martinez, S.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York, NY IEEE 01.01.2012 Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptative systems Algorithm design and analysis Algorithms Applied sciences Asymptotic properties Automatic control Computer science; control theory; systems Control theory. Systems Convergence Convex functions Cooperative control distributed optimization Exact sciences and technology Heuristic algorithms Inequalities Lagrangian functions multi-agent systems Network topology Networks Optimal control Optimization Saddle points Studies multi-agent systems Subgradient optimization distributed optimization Cooperative control Transmission protocol Duality Topology Adaptive control Convex programming Saddle point Penalty function Multiagent system Cooperation Distributed algorithm Inequality constraint Equality constraint Primal dual method Distributed control Asymptotic approximation Objective function Lagrangian function
ISSN:	0018-9286, 1558-2523
Online-Zugang:	Volltext
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