Distributed event-triggered algorithm for convex optimization with coupled constraints

This paper develops a distributed primal–dual algorithm via an event-triggered mechanism to solve a class of convex optimization problems subject to local set constraints, coupled equality and inequality constraints. Different from some existing distributed algorithms with the diminishing step-sizes...

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Veröffentlicht in:Automatica (Oxford) Jg. 170; S. 111877
Hauptverfasser: Huang, Yi, Zeng, Xianlin, Sun, Jian, Meng, Ziyang
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Elsevier Ltd 01.12.2024
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ISSN:0005-1098
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Abstract This paper develops a distributed primal–dual algorithm via an event-triggered mechanism to solve a class of convex optimization problems subject to local set constraints, coupled equality and inequality constraints. Different from some existing distributed algorithms with the diminishing step-sizes, our algorithm uses the constant step-sizes, and is shown to achieve an exact convergence to an optimal solution with an ergodic convergence rate of O(1/k) for general convex objective functions, where k>0 is the iteration number. Based on the event-triggered communication mechanism, the proposed algorithm can effectively reduce the communication cost without sacrificing the convergence rate. Finally, a numerical example is presented to verify the effectiveness of the proposed algorithm.
AbstractList This paper develops a distributed primal–dual algorithm via an event-triggered mechanism to solve a class of convex optimization problems subject to local set constraints, coupled equality and inequality constraints. Different from some existing distributed algorithms with the diminishing step-sizes, our algorithm uses the constant step-sizes, and is shown to achieve an exact convergence to an optimal solution with an ergodic convergence rate of O(1/k) for general convex objective functions, where k>0 is the iteration number. Based on the event-triggered communication mechanism, the proposed algorithm can effectively reduce the communication cost without sacrificing the convergence rate. Finally, a numerical example is presented to verify the effectiveness of the proposed algorithm.
ArticleNumber 111877
Author Meng, Ziyang
Huang, Yi
Sun, Jian
Zeng, Xianlin
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  surname: Huang
  fullname: Huang, Yi
  email: yihuang@bit.edu.cn
  organization: State Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China
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  givenname: Xianlin
  surname: Zeng
  fullname: Zeng, Xianlin
  email: xianlin.zeng@bit.edu.cn
  organization: State Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China
– sequence: 3
  givenname: Jian
  surname: Sun
  fullname: Sun, Jian
  email: sunjian@bit.edu.cn
  organization: State Key Lab of Autonomous Intelligent Unmanned Systems, Beijing Institute of Technology, Beijing 100081, China
– sequence: 4
  givenname: Ziyang
  surname: Meng
  fullname: Meng, Ziyang
  email: ziyangmeng@mail.tsinghua.edu.cn
  organization: Department of Precision Instrument, Tsinghua University, Beijing 100084, China
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Keywords Constant step-sizes
Distributed optimization
Event-triggered communication
Coupled constraints
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Snippet This paper develops a distributed primal–dual algorithm via an event-triggered mechanism to solve a class of convex optimization problems subject to local set...
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StartPage 111877
SubjectTerms Constant step-sizes
Coupled constraints
Distributed optimization
Event-triggered communication
Title Distributed event-triggered algorithm for convex optimization with coupled constraints
URI https://dx.doi.org/10.1016/j.automatica.2024.111877
Volume 170
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